yukun-hh/Kaggle
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
fc30281b3ec56b7098bb0cf7efcc516d67b8bb15
Kaggle/Natural-Language-Processing-with-Disaster-Tweets/main.ipynb
T

3637 lines
135 KiB
Plaintext
Raw Normal View History

非kaggle内容 一些自学的模型
2026-08-18 23:21:35 +08:00
{
"cells": [
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": [
"import pandas as pd\n",
"import torch\n",
"import torch.nn as nn\n",
"from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
"from torch.utils.data import Dataset, DataLoader"
],
"id": "b90fab9688c875b3"
},
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": [
"train_df = pd.read_csv('/kaggle/input/competitions/nlp-getting-started/train.csv')\n",
"test_df = pd.read_csv('/kaggle/input/competitions/nlp-getting-started/test.csv')\n",
"from sklearn.model_selection import train_test_split\n",
"train_df, val_df = train_test_split(train_df, test_size=0.1, random_state=42)\n",
"print(f\"Train: {len(train_df)}, Val: {len(val_df)}, Test: {len(test_df)}\")"
],
"id": "d07abe4465837f46"
},
{
"cell_type": "code",
"execution_count": 4,
"id": "2c6d716d",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T02:00:25.795637Z",
"iopub.status.busy": "2026-07-22T02:00:25.794874Z",
"iopub.status.idle": "2026-07-22T02:00:43.802371Z",
"shell.execute_reply": "2026-07-22T02:00:43.798282Z"
},
"papermill": {
"duration": 18.250754,
"end_time": "2026-07-22T02:00:44.042750+00:00",
"exception": false,
"start_time": "2026-07-22T02:00:25.791996+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ad6193cf97eb4883bd1c6bd0b49cd4e1",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"config.json: 0%| | 0.00/616 [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f2dc334807a54ebcb8a2bcd042a29b7b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"tokenizer_config.json: 0%| | 0.00/25.0 [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "4132e2c0c15c464abc7f0eb0a3b8557e",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"sentencepiece.bpe.model: 0%| | 0.00/5.07M [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "cf852d7b51bf487eb170ef2b8c931fec",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"tokenizer.json: 0.00B [00:00, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "afa1982d4c894d14afc9c364045b42be",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"model.safetensors: 0%| | 0.00/2.24G [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ef675f8da7c44aa8aa1b8829a4e8fd24",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Loading weights: 0%| | 0/389 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"XLMRobertaForSequenceClassification LOAD REPORT from: xlm-roberta-large\n",
"Key | Status | \n",
"----------------------------+------------+-\n",
"lm_head.dense.weight | UNEXPECTED | \n",
"lm_head.dense.bias | UNEXPECTED | \n",
"lm_head.bias | UNEXPECTED | \n",
"roberta.pooler.dense.weight | UNEXPECTED | \n",
"roberta.pooler.dense.bias | UNEXPECTED | \n",
"lm_head.layer_norm.bias | UNEXPECTED | \n",
"lm_head.layer_norm.weight | UNEXPECTED | \n",
"classifier.dense.weight | MISSING | \n",
"classifier.dense.bias | MISSING | \n",
"classifier.out_proj.weight | MISSING | \n",
"classifier.out_proj.bias | MISSING | \n",
"\n",
"Notes:\n",
"- UNEXPECTED\t:can be ignored when loading from different task/architecture; not ok if you expect identical arch.\n",
"- MISSING\t:those params were newly initialized because missing from the checkpoint. Consider training on your downstream task.\n"
]
}
],
"source": [
"model_name = \"xlm-roberta-large\"\n",
"tokenizer = AutoTokenizer.from_pretrained(model_name)\n",
"model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "cac7fc28",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T02:00:44.049341Z",
"iopub.status.busy": "2026-07-22T02:00:44.048999Z",
"iopub.status.idle": "2026-07-22T02:00:44.057828Z",
"shell.execute_reply": "2026-07-22T02:00:44.057304Z"
},
"papermill": {
"duration": 0.013673,
"end_time": "2026-07-22T02:00:44.059132+00:00",
"exception": false,
"start_time": "2026-07-22T02:00:44.045459+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": [
"import numpy as np\n",
"class NliDataset(Dataset):\n",
" def __init__(self, df, tokenizer, max_length=128):\n",
" self.df = df.reset_index(drop=True)\n",
" self.tokenizer = tokenizer\n",
" self.max_length = max_length\n",
"\n",
" def __len__(self):\n",
" return len(self.df)\n",
"\n",
" def __getitem__(self, idx):\n",
" row = self.df.iloc[idx]\n",
" strs=''\n",
" if row['keyword'] is not np.nan:\n",
" strs=strs+'['+row['keyword']+']'\n",
" if row['location'] is not np.nan:\n",
" strs=strs+'['+row['location']+']'\n",
" strs=strs+row['text']\n",
" encoding = self.tokenizer(\n",
" strs,\n",
" truncation=True,\n",
" padding='max_length',\n",
" max_length=self.max_length,\n",
" return_tensors='pt' # 返回 PyTorch Tensor\n",
" )\n",
" # 去掉 batch 维度（因为只处理单条）\n",
" item = {\n",
" 'input_ids': encoding['input_ids'].squeeze(0),\n",
" 'attention_mask': encoding['attention_mask'].squeeze(0)\n",
" }\n",
" if 'target' in row:\n",
" item['labels'] = torch.tensor(row['target'], dtype=torch.long)\n",
" return item\n",
"\n",
"batch_size = 16 # 根据显存调整，推荐使用 16 或 32\n",
"max_length = 128\n",
"\n",
"train_dataset = NliDataset(train_df, tokenizer, max_length)\n",
"val_dataset = NliDataset(val_df, tokenizer, max_length)\n",
"\n",
"train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n",
"val_loader = DataLoader(val_dataset, batch_size=batch_size, shuffle=False)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "48f88e0c",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T02:00:44.065561Z",
"iopub.status.busy": "2026-07-22T02:00:44.065354Z",
"iopub.status.idle": "2026-07-22T02:00:44.073182Z",
"shell.execute_reply": "2026-07-22T02:00:44.072432Z"
},
"papermill": {
"duration": 0.013598,
"end_time": "2026-07-22T02:00:44.075169+00:00",
"exception": false,
"start_time": "2026-07-22T02:00:44.061571+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"classifier.dense.weight: requires_grad = True\n",
"classifier.dense.bias: requires_grad = True\n",
"classifier.out_proj.weight: requires_grad = True\n",
"classifier.out_proj.bias: requires_grad = True\n",
"roberta.embeddings.word_embeddings.weight: requires_grad = True\n",
"roberta.embeddings.token_type_embeddings.weight: requires_grad = True\n",
"roberta.embeddings.LayerNorm.weight: requires_grad = True\n",
"roberta.embeddings.LayerNorm.bias: requires_grad = True\n",
"roberta.embeddings.position_embeddings.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.0.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.0.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.0.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.0.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.0.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.0.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.0.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.0.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.0.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.1.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.1.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.1.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.1.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.1.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.1.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.1.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.1.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.1.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.1.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.1.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.2.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.2.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.2.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.2.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.2.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.2.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.2.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.2.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.2.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.2.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.2.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.3.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.3.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.3.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.3.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.3.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.3.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.3.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.3.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.3.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.3.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.3.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.4.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.4.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.4.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.4.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.4.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.4.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.4.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.4.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.4.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.4.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.4.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.5.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.5.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.5.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.5.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.5.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.5.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.5.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.5.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.5.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.5.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.5.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.6.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.6.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.6.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.6.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.6.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.6.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.6.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.6.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.6.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.6.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.6.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.7.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.7.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.7.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.7.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.7.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.7.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.7.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.7.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.7.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.7.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.7.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.8.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.8.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.8.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.8.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.8.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.8.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.8.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.8.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.8.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.8.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.8.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.9.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.9.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.9.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.9.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.9.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.9.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.9.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.9.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.9.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.9.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.9.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.10.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.10.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.10.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.10.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.10.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.10.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.10.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.10.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.10.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.10.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.10.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.11.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.11.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.11.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.11.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.11.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.11.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.11.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.11.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.11.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.11.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.11.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.12.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.12.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.12.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.12.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.12.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.12.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.12.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.12.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.12.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.12.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.12.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.13.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.13.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.13.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.13.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.13.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.13.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.13.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.13.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.13.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.13.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.13.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.14.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.14.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.14.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.14.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.14.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.14.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.14.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.14.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.14.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.14.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.14.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.15.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.15.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.15.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.15.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.15.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.15.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.15.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.15.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.15.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.15.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.15.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.16.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.16.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.16.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.16.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.16.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.16.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.16.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.16.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.16.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.16.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.16.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.17.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.17.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.17.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.17.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.17.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.17.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.17.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.17.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.17.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.17.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.17.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.18.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.18.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.18.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.18.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.18.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.18.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.18.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.18.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.18.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.18.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.18.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.19.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.19.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.19.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.19.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.19.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.19.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.19.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.19.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.19.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.19.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.19.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.20.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.20.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.20.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.20.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.20.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.20.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.20.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.20.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.20.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.20.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.20.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.21.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.21.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.21.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.21.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.21.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.21.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.21.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.21.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.21.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.21.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.21.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.22.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.22.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.22.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.22.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.22.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.22.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.22.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.22.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.22.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.22.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.22.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.query.weight: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.query.bias: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.key.weight: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.key.bias: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.value.weight: requires_grad = True\n",
"roberta.encoder.layer.23.attention.self.value.bias: requires_grad = True\n",
"roberta.encoder.layer.23.attention.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.23.attention.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.23.attention.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.23.attention.output.LayerNorm.bias: requires_grad = True\n",
"roberta.encoder.layer.23.intermediate.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.23.intermediate.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.23.output.dense.weight: requires_grad = True\n",
"roberta.encoder.layer.23.output.dense.bias: requires_grad = True\n",
"roberta.encoder.layer.23.output.LayerNorm.weight: requires_grad = True\n",
"roberta.encoder.layer.23.output.LayerNorm.bias: requires_grad = True\n"
]
}
],
"source": [
"for name, param in model.named_parameters():\n",
" #if param.requires_grad:\n",
" print(f\"{name}: requires_grad = {param.requires_grad}\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "a24b83a5",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T02:00:44.082499Z",
"iopub.status.busy": "2026-07-22T02:00:44.081954Z",
"iopub.status.idle": "2026-07-22T02:00:59.414269Z",
"shell.execute_reply": "2026-07-22T02:00:59.413336Z"
},
"papermill": {
"duration": 15.338053,
"end_time": "2026-07-22T02:00:59.416223+00:00",
"exception": false,
"start_time": "2026-07-22T02:00:44.078170+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting torchao==0.16.0\r\n",
" Downloading torchao-0.16.0-cp310-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.metadata (20 kB)\r\n",
"Downloading torchao-0.16.0-cp310-abi3-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (3.2 MB)\r\n",
"\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m3.2/3.2 MB\u001B[0m \u001B[31m47.8 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\r\n",
"\u001B[?25hInstalling collected packages: torchao\r\n",
" Attempting uninstall: torchao\r\n",
" Found existing installation: torchao 0.10.0\r\n",
" Uninstalling torchao-0.10.0:\r\n",
" Successfully uninstalled torchao-0.10.0\r\n",
"Successfully installed torchao-0.16.0\r\n",
"验证分类器参数是否被训练:\n",
"base_model.model.classifier.modules_to_save.default.dense.weight: requires_grad = True\n",
"base_model.model.classifier.modules_to_save.default.dense.bias: requires_grad = True\n",
"base_model.model.classifier.modules_to_save.default.out_proj.weight: requires_grad = True\n",
"base_model.model.classifier.modules_to_save.default.out_proj.bias: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.8.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.8.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.8.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.8.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.9.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.9.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.9.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.9.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.10.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.10.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.10.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.10.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.11.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.11.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.11.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.11.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.12.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.12.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.12.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.12.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.13.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.13.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.13.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.13.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.14.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.14.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.14.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.14.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.15.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.15.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.15.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.15.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.16.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.16.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.16.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.16.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.17.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.17.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.17.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.17.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.18.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.18.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.18.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.18.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.19.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.19.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.19.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.19.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.20.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.20.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.20.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.20.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.21.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.21.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.21.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.21.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.22.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.22.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.22.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.22.attention.self.value.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.23.attention.self.query.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.23.attention.self.query.lora_B.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.23.attention.self.value.lora_A.default.weight: requires_grad = True\n",
"base_model.model.roberta.encoder.layer.23.attention.self.value.lora_B.default.weight: requires_grad = True\n"
]
}
],
"source": [
"!pip install torchao==0.16.0\n",
"from peft import LoraConfig, get_peft_model\n",
"target_layers = [8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]\n",
"target_modules=[]\n",
"for layer in target_layers:\n",
" target_modules.append(f\"roberta.encoder.layer.{layer}.attention.self.query\")\n",
" target_modules.append(f\"roberta.encoder.layer.{layer}.attention.self.value\")\n",
"# 配置 LoRA\n",
"config = LoraConfig(\n",
" r=8, # LoRA 的秩\n",
" lora_alpha=16, # LoRA 的缩放因子\n",
" target_modules=target_modules, # 目标模块\n",
" lora_dropout=0.1, # Dropout 概率\n",
" bias=\"none\", # 是否更新偏置\n",
" modules_to_save=[\"classifier\"], # 指定分类器需要被微调\n",
")\n",
"\n",
"# 封装为 LoRA 模型\n",
"model = get_peft_model(model, config)\n",
"\n",
"# 验证分类器是否被微调\n",
"print(\"验证分类器参数是否被训练:\")\n",
"for name, param in model.named_parameters():\n",
" if param.requires_grad:\n",
" print(f\"{name}: requires_grad = {param.requires_grad}\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "8082471f",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T02:00:59.424781Z",
"iopub.status.busy": "2026-07-22T02:00:59.424534Z",
"iopub.status.idle": "2026-07-22T04:19:30.137552Z",
"shell.execute_reply": "2026-07-22T04:19:30.136572Z"
},
"papermill": {
"duration": 8310.719504,
"end_time": "2026-07-22T04:19:30.139354+00:00",
"exception": false,
"start_time": "2026-07-22T02:00:59.419850+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 1/30: 100%|██████████| 429/429 [04:15<00:00, 1.68it/s, loss=0.5541, avg_loss=0.4941]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1 train_loss: 0.4941\n",
"acc:0.8070865869522095\n",
"best model save,acc:0.8070865869522095\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 2/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.1806, avg_loss=0.4009]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 2 train_loss: 0.4009\n",
"acc:0.8280839920043945\n",
"best model save,acc:0.8280839920043945\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 3/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0178, avg_loss=0.3768]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 3 train_loss: 0.3768\n",
"acc:0.8320209980010986\n",
"best model save,acc:0.8320209980010986\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 4/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0461, avg_loss=0.3544]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 4 train_loss: 0.3544\n",
"acc:0.8359580039978027\n",
"best model save,acc:0.8359580039978027\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 5/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0868, avg_loss=0.3336]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 5 train_loss: 0.3336\n",
"acc:0.8320209980010986\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 6/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=1.1006, avg_loss=0.3171]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 6 train_loss: 0.3171\n",
"acc:0.847769021987915\n",
"best model save,acc:0.847769021987915\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 7/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.1015, avg_loss=0.2971]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 7 train_loss: 0.2971\n",
"acc:0.8372703194618225\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 8/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.1445, avg_loss=0.2843]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 8 train_loss: 0.2843\n",
"acc:0.8333333134651184\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 9/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=1.0584, avg_loss=0.2712]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 9 train_loss: 0.2712\n",
"acc:0.8359580039978027\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 10/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0560, avg_loss=0.2626]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 10 train_loss: 0.2626\n",
"acc:0.8372703194618225\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 11/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.5303, avg_loss=0.2645]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 11 train_loss: 0.2645\n",
"acc:0.8372703194618225\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 12/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.7138, avg_loss=0.2643]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 12 train_loss: 0.2643\n",
"acc:0.8359580039978027\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 13/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0551, avg_loss=0.2616]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 13 train_loss: 0.2616\n",
"acc:0.8438320159912109\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 14/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.8738, avg_loss=0.2686]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 14 train_loss: 0.2686\n",
"acc:0.8293963074684143\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 15/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.1841, avg_loss=0.2672]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 15 train_loss: 0.2672\n",
"acc:0.8202099800109863\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 16/30: 100%|██████████| 429/429 [04:21<00:00, 1.64it/s, loss=0.0475, avg_loss=0.2644]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 16 train_loss: 0.2644\n",
"acc:0.8398950099945068\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 17/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0248, avg_loss=0.2637]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 17 train_loss: 0.2637\n",
"acc:0.8228346705436707\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 18/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.1059, avg_loss=0.2565]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 18 train_loss: 0.2565\n",
"acc:0.8385826945304871\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 19/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0538, avg_loss=0.2459]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 19 train_loss: 0.2459\n",
"acc:0.8372703194618225\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 20/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.1534, avg_loss=0.2406]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 20 train_loss: 0.2406\n",
"acc:0.8070865869522095\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 21/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0568, avg_loss=0.2275]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 21 train_loss: 0.2275\n",
"acc:0.8110235929489136\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 22/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0785, avg_loss=0.2072]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 22 train_loss: 0.2072\n",
"acc:0.8280839920043945\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 23/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.4414, avg_loss=0.2021]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 23 train_loss: 0.2021\n",
"acc:0.8241469860076904\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 24/30: 100%|██████████| 429/429 [04:20<00:00, 1.65it/s, loss=0.0444, avg_loss=0.1876]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 24 train_loss: 0.1876\n",
"acc:0.8267716765403748\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 25/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0273, avg_loss=0.1657]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 25 train_loss: 0.1657\n",
"acc:0.8215222954750061\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 26/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0044, avg_loss=0.1466]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 26 train_loss: 0.1466\n",
"acc:0.8241469860076904\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 27/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0474, avg_loss=0.1297]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 27 train_loss: 0.1297\n",
"acc:0.8188976049423218\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 28/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0006, avg_loss=0.1282]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 28 train_loss: 0.1282\n",
"acc:0.8228346705436707\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 29/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0009, avg_loss=0.1116]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 29 train_loss: 0.1116\n",
"acc:0.8228346705436707\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Epoch 30/30: 100%|██████████| 429/429 [04:19<00:00, 1.65it/s, loss=0.0992, avg_loss=0.1074]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 30 train_loss: 0.1074\n",
"acc:0.8228346705436707\n"
]
}
],
"source": [
"@torch.no_grad()\n",
"def validate(model,loader):\n",
" model.eval()\n",
" acc=0\n",
" total=0\n",
" for batch in loader:\n",
" input_ids = batch['input_ids'].to(device)\n",
" attention_mask = batch['attention_mask'].to(device)\n",
" labels = batch['labels'].to(device)\n",
" outputs = model(input_ids, attention_mask=attention_mask).logits\n",
" pred=torch.argmax(outputs,dim=1)\n",
" acc+=pred.eq(labels).sum()\n",
" total+=labels.size(0)\n",
" print(f\"acc:{acc/total}\")\n",
" return acc/total\n",
"from tqdm import tqdm \n",
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
"model=model.to(device)\n",
"loss_func = nn.CrossEntropyLoss()\n",
"optimizer = torch.optim.AdamW(model.parameters(), lr=2e-4)\n",
"scheduler=torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=10)\n",
"epochs = 30\n",
"best_acc=0.0\n",
"for epoch in range(epochs):\n",
" model.train()\n",
" training_loss = 0\n",
" \n",
" # 使用 tqdm 包装 dataloader，并设置描述信息\n",
" progress_bar = tqdm(train_loader, desc=f\"Epoch {epoch+1}/{epochs}\")\n",
" lens=0\n",
" for batch in progress_bar:\n",
" optimizer.zero_grad()\n",
" input_ids = batch['input_ids'].to(device)\n",
" attention_mask = batch['attention_mask'].to(device)\n",
" labels = batch['labels'].to(device)\n",
" outputs = model(input_ids, attention_mask=attention_mask).logits\n",
" loss = loss_func(outputs, labels)\n",
" loss.backward()\n",
" optimizer.step()\n",
" \n",
" training_loss += loss.item()\n",
" lens+=1\n",
" # 更新进度条显示当前 batch 的损失\n",
" progress_bar.set_postfix({\n",
" 'loss': f'{loss.item():.4f}',\n",
" 'avg_loss': f'{training_loss / (progress_bar.n+1):.4f}' # progress_bar.n 是已处理 batch 数\n",
" })\n",
" \n",
" scheduler.step()\n",
" \n",
" avg_train_loss = training_loss / lens\n",
" print(f\"Epoch {epoch+1} train_loss: {avg_train_loss:.4f}\")\n",
" \n",
" # 验证（你也可以为验证添加进度条，见下方建议）\n",
" current_acc=validate(model, val_loader)\n",
" if current_acc > best_acc :\n",
" torch.save(model.state_dict(), 'model.pth')\n",
" print(f\"best model save,acc:{current_acc}\")\n",
" best_acc=current_acc"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "61693fae",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-22T04:19:32.122431Z",
"iopub.status.busy": "2026-07-22T04:19:32.121674Z",
"iopub.status.idle": "2026-07-22T04:20:44.644578Z",
"shell.execute_reply": "2026-07-22T04:20:44.643783Z"
},
"papermill": {
"duration": 74.494369,
"end_time": "2026-07-22T04:20:45.673202+00:00",
"exception": false,
"start_time": "2026-07-22T04:19:31.178833+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" id target\n",
"0 0 1\n",
"1 2 1\n",
"2 3 1\n",
"3 9 1\n",
"4 11 1\n",
"... ... ...\n",
"3258 10861 0\n",
"3259 10865 1\n",
"3260 10868 1\n",
"3261 10874 1\n",
"3262 10875 1\n",
"\n",
"[3263 rows x 2 columns]\n",
"Submission saved!\n"
]
}
],
"source": [
"test_dataset = NliDataset(test_df, tokenizer, max_length)\n",
"test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False)\n",
"all_preds=[]\n",
"model.load_state_dict(torch.load('model.pth'))\n",
"model.eval()\n",
"with torch.no_grad():\n",
" for batch in test_loader:\n",
" input_ids = batch['input_ids'].to(device)\n",
" attention_mask = batch['attention_mask'].to(device)\n",
" outputs = model(input_ids, attention_mask=attention_mask).logits\n",
" preds = torch.argmax(outputs, dim=1)\n",
" all_preds.extend(preds.cpu().numpy())\n",
"\n",
"submission = pd.DataFrame({\n",
" 'id':test_df['id'],\n",
" 'target': all_preds\n",
"})\n",
"\n",
"print(submission)\n",
"submission.to_csv('submission.csv', index=False)\n",
"print(\"Submission saved!\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "900e4ba5",
"metadata": {
"papermill": {
"duration": 0.946718,
"end_time": "2026-07-22T04:20:47.646925+00:00",
"exception": false,
"start_time": "2026-07-22T04:20:46.700207+00:00",
"status": "completed"
},
"tags": []
},
"outputs": [],
"source": []
}
],
"metadata": {
"kaggle": {
"accelerator": "none",
"dataSources": [],
"dockerImageVersionId": 28755,
"isGpuEnabled": false,
"isInternetEnabled": false,
"language": "python",
"sourceType": "notebook"
},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.13"
},
"papermill": {
"default_parameters": {},
"duration": 8457.820464,
"end_time": "2026-07-22T04:20:52.588673+00:00",
"environment_variables": {},
"exception": null,
"input_path": "__notebook__.ipynb",
"output_path": "__notebook__.ipynb",
"parameters": {},
"start_time": "2026-07-22T01:59:54.768209+00:00",
"version": "2.7.0"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {
"090c40f079f7433e9069e304e0dbb2b5": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0a94a2b0b5e5450eaac3b8771917ae84": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_b4c67109ed144306a156834426f85b77",
"max": 389.0,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_432c82cbc9b84044b68645bb220bde16",
"tabbable": null,
"tooltip": null,
"value": 389.0
}
},
"0ce9c293dd84435b86512d4f378ad612": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1a69ec693f834e35a3ed83fcd7d98422": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_0ce9c293dd84435b86512d4f378ad612",
"placeholder": "​",
"style": "IPY_MODEL_8a8adda41d63458cb58a40e20b50ee78",
"tabbable": null,
"tooltip": null,
"value": " 5.07M/5.07M [00:00&lt;00:00, 15.4MB/s]"
}
},
"1e9adab8920b40ceaeb4b063f0a5a3db": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_8cdfe320f8f74e25ae31dd4ae75ccf46",
"placeholder": "​",
"style": "IPY_MODEL_dc07462ca4034c1a8b82821ce049d638",
"tabbable": null,
"tooltip": null,
"value": "Loading weights: 100%"
}
},
"26c66cc4cae74ab7b611c1425ffe333a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"2957f62682394c2f95cf8876f243f236": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"2fd55f67774149cf932c9554929f40b9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"3408d897d7c4403f99b6c576c569833c": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"3b6a8c48ef4b4e76bab91161ecdc9a40": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_73678a7e38e546228273c9ce4d1dd750",
"max": 1.0,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_d1281ac7c62f44ca9234c6332a7b6cf5",
"tabbable": null,
"tooltip": null,
"value": 1.0
}
},
"3d8a4241d2624055878163b65577e003": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_b902fea558094e6c8b9fc2cd026bbd0e",
"placeholder": "​",
"style": "IPY_MODEL_5e0dc86420964900af197ee1de5e16e1",
"tabbable": null,
"tooltip": null,
"value": " 25.0/25.0 [00:00&lt;00:00, 3.31kB/s]"
}
},
"3f066f23751d42dcb32207f28b9bfd5f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_777e133b489e4a2fa5a08fe55312bb5a",
"placeholder": "​",
"style": "IPY_MODEL_3408d897d7c4403f99b6c576c569833c",
"tabbable": null,
"tooltip": null,
"value": "tokenizer_config.json: 100%"
}
},
"4132e2c0c15c464abc7f0eb0a3b8557e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_8d5c0298f9264814a668f540380036e1",
"IPY_MODEL_e4cd93623daf4fe78e3bf47b89b1345f",
"IPY_MODEL_1a69ec693f834e35a3ed83fcd7d98422"
],
"layout": "IPY_MODEL_d133db57516f43e7847557e8625771df",
"tabbable": null,
"tooltip": null
}
},
"432c82cbc9b84044b68645bb220bde16": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"482469099e2e4cb5a39447406e56cff0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"508e5b14f8804bcf905c2d37f9dbea31": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_e7eb78ea55134e44b53ad4ba13e847cd",
"placeholder": "​",
"style": "IPY_MODEL_84a66d7860de48d991754c61b3e65660",
"tabbable": null,
"tooltip": null,
"value": "model.safetensors: 100%"
}
},
"546d10a484304b2f943822b2eeec64ee": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"57ad1d5e68064863bd1a6de202ae0e9d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"5e0dc86420964900af197ee1de5e16e1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"60e1ba288fab4685b8e91ab575e7a50b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_26c66cc4cae74ab7b611c1425ffe333a",
"placeholder": "​",
"style": "IPY_MODEL_90d5d9ea21e34c1b9424531650fb3f80",
"tabbable": null,
"tooltip": null,
"value": " 616/616 [00:00&lt;00:00, 55.8kB/s]"
}
},
"645b2985951b4bff83b02085b9e36be8": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"685fffe09d3340d3bdd8549273788f58": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_bda6a531e6d749e28407cfcbb6fbb98c",
"max": 2.244817354E9,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_645b2985951b4bff83b02085b9e36be8",
"tabbable": null,
"tooltip": null,
"value": 2.244817354E9
}
},
"6972c432d03c41da9c2bbb0b25fcf832": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_dcef267d7dc44a279ae8ed5e6a1cabfe",
"placeholder": "​",
"style": "IPY_MODEL_2957f62682394c2f95cf8876f243f236",
"tabbable": null,
"tooltip": null,
"value": "config.json: 100%"
}
},
"73678a7e38e546228273c9ce4d1dd750": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": "20px"
}
},
"73ce65eea94e41129c78fc60d6481c07": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"777e133b489e4a2fa5a08fe55312bb5a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"84a66d7860de48d991754c61b3e65660": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"87da9ab002614424a07e5fbcff86f375": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"8920fc3433494e9d97c670223041845f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"8a8adda41d63458cb58a40e20b50ee78": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"8cdfe320f8f74e25ae31dd4ae75ccf46": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"8d5c0298f9264814a668f540380036e1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_546d10a484304b2f943822b2eeec64ee",
"placeholder": "​",
"style": "IPY_MODEL_482469099e2e4cb5a39447406e56cff0",
"tabbable": null,
"tooltip": null,
"value": "sentencepiece.bpe.model: 100%"
}
},
"9098d933dd8d48f186c47d58a13546aa": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"90d5d9ea21e34c1b9424531650fb3f80": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"97f5798b5f5e444dafa36fa55e951e84": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_fe886471368e49dea688303ec14f2dcf",
"max": 25.0,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_57ad1d5e68064863bd1a6de202ae0e9d",
"tabbable": null,
"tooltip": null,
"value": 25.0
}
},
"a1f7705d0e594d97bf5393917f6113e9": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_e6856331e9514cbb8e6c81940301de36",
"placeholder": "​",
"style": "IPY_MODEL_f27e863469d947bdadbaf7cc36aa4a07",
"tabbable": null,
"tooltip": null,
"value": " 389/389 [00:00&lt;00:00, 921.59it/s, Materializing param=roberta.encoder.layer.23.output.dense.weight]"
}
},
"a27cfe6dfd714cf5bea035f399d714f1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_090c40f079f7433e9069e304e0dbb2b5",
"max": 616.0,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_8920fc3433494e9d97c670223041845f",
"tabbable": null,
"tooltip": null,
"value": 616.0
}
},
"ad6193cf97eb4883bd1c6bd0b49cd4e1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_6972c432d03c41da9c2bbb0b25fcf832",
"IPY_MODEL_a27cfe6dfd714cf5bea035f399d714f1",
"IPY_MODEL_60e1ba288fab4685b8e91ab575e7a50b"
],
"layout": "IPY_MODEL_9098d933dd8d48f186c47d58a13546aa",
"tabbable": null,
"tooltip": null
}
},
"afa1982d4c894d14afc9c364045b42be": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_508e5b14f8804bcf905c2d37f9dbea31",
"IPY_MODEL_685fffe09d3340d3bdd8549273788f58",
"IPY_MODEL_f9828122690848528a82610b7b75522d"
],
"layout": "IPY_MODEL_bbcb8b483c114842974359143040d5be",
"tabbable": null,
"tooltip": null
}
},
"b4c67109ed144306a156834426f85b77": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"b902fea558094e6c8b9fc2cd026bbd0e": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"bbcb8b483c114842974359143040d5be": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"bda6a531e6d749e28407cfcbb6fbb98c": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"c8ffc4357ebc470aa2b22549a8fb39d9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"cf852d7b51bf487eb170ef2b8c931fec": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_e4101a49237e40f7abe37305cdd01fde",
"IPY_MODEL_3b6a8c48ef4b4e76bab91161ecdc9a40",
"IPY_MODEL_f0acf536573e44f6bfbdfd775631a1b1"
],
"layout": "IPY_MODEL_ea86faa0f63f4d36b31c3db7aad7f88c",
"tabbable": null,
"tooltip": null
}
},
"cf96198e48754787bfd396d20766af80": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"d1281ac7c62f44ca9234c6332a7b6cf5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"d133db57516f43e7847557e8625771df": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"d63c11434da54d1a8326a07e3a48c856": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"dc07462ca4034c1a8b82821ce049d638": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"dcef267d7dc44a279ae8ed5e6a1cabfe": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"de49874254e148d4ab45810d9350d20b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"e072c50271264b1197d32377d851584e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"e4101a49237e40f7abe37305cdd01fde": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_2fd55f67774149cf932c9554929f40b9",
"placeholder": "​",
"style": "IPY_MODEL_ea773336a62d4f5096c9c9ceb01fce39",
"tabbable": null,
"tooltip": null,
"value": "tokenizer.json: "
}
},
"e4cd93623daf4fe78e3bf47b89b1345f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_de49874254e148d4ab45810d9350d20b",
"max": 5069051.0,
"min": 0.0,
"orientation": "horizontal",
"style": "IPY_MODEL_fd04cd65456646dabf5d22afd04b7e95",
"tabbable": null,
"tooltip": null,
"value": 5069051.0
}
},
"e6856331e9514cbb8e6c81940301de36": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"e7eb78ea55134e44b53ad4ba13e847cd": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"ea773336a62d4f5096c9c9ceb01fce39": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"ea86faa0f63f4d36b31c3db7aad7f88c": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"ef675f8da7c44aa8aa1b8829a4e8fd24": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_1e9adab8920b40ceaeb4b063f0a5a3db",
"IPY_MODEL_0a94a2b0b5e5450eaac3b8771917ae84",
"IPY_MODEL_a1f7705d0e594d97bf5393917f6113e9"
],
"layout": "IPY_MODEL_87da9ab002614424a07e5fbcff86f375",
"tabbable": null,
"tooltip": null
}
},
"f0acf536573e44f6bfbdfd775631a1b1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_73ce65eea94e41129c78fc60d6481c07",
"placeholder": "​",
"style": "IPY_MODEL_e072c50271264b1197d32377d851584e",
"tabbable": null,
"tooltip": null,
"value": " 9.10M/? [00:00&lt;00:00, 21.0MB/s]"
}
},
"f27e863469d947bdadbaf7cc36aa4a07": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"background": null,
"description_width": "",
"font_size": null,
"text_color": null
}
},
"f2dc334807a54ebcb8a2bcd042a29b7b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_3f066f23751d42dcb32207f28b9bfd5f",
"IPY_MODEL_97f5798b5f5e444dafa36fa55e951e84",
"IPY_MODEL_3d8a4241d2624055878163b65577e003"
],
"layout": "IPY_MODEL_c8ffc4357ebc470aa2b22549a8fb39d9",
"tabbable": null,
"tooltip": null
}
},
"f9828122690848528a82610b7b75522d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "2.0.0",
"_view_name": "HTMLView",
"description": "",
"description_allow_html": false,
"layout": "IPY_MODEL_cf96198e48754787bfd396d20766af80",
"placeholder": "​",
"style": "IPY_MODEL_d63c11434da54d1a8326a07e3a48c856",
"tabbable": null,
"tooltip": null,
"value": " 2.24G/2.24G [00:10&lt;00:00, 602MB/s]"
}
},
"fd04cd65456646dabf5d22afd04b7e95": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "2.0.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"fe886471368e49dea688303ec14f2dcf": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "2.0.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "2.0.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border_bottom": null,
"border_left": null,
"border_right": null,
"border_top": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
}
},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Reference in New Issue Copy Permalink