Instructions to use osiria/bert-italian-uncased-question-answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osiria/bert-italian-uncased-question-answering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="osiria/bert-italian-uncased-question-answering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("osiria/bert-italian-uncased-question-answering") model = AutoModelForQuestionAnswering.from_pretrained("osiria/bert-italian-uncased-question-answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload osiria_bert_italian_uncased_qa_evaluation.ipynb
Browse files
osiria_bert_italian_uncased_qa_evaluation.ipynb
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"metadata": {
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"colab": {
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"provenance": [],
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"cell_type": "markdown",
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"source": [
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"# osiria/bert-italian-cased-question-answering\n",
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"## test set metrics"
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],
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"metadata": {
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"id": "oub2ir8ZDkrH"
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "02K9xO6Gvto1",
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"outputId": "6adbc718-df6a-437d-eb07-d67404f9cd2b"
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Collecting git+https://github.com/huggingface/transformers\n",
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" Cloning https://github.com/huggingface/transformers to /tmp/pip-req-build-m860w1jf\n",
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" Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-m860w1jf\n",
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" Resolved https://github.com/huggingface/transformers to commit df5c5c62ae253055336f5bb0828ca8e3e15ab6bd\n",
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" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
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" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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"Building wheels for collected packages: transformers\n",
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" Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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" Created wheel for transformers: filename=transformers-4.36.0.dev0-py3-none-any.whl size=8195433 sha256=c5e14f23bb3ae5edc677f78f448f1a67a961992c880e0441c99cb6f4db9469cf\n",
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" Stored in directory: /tmp/pip-ephem-wheel-cache-ytzg25y9/wheels/c0/14/d6/6c9a5582d2ac191ec0a483be151a4495fe1eb2a6706ca49f1b\n",
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"Successfully built transformers\n",
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"Installing collected packages: transformers\n",
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" Attempting uninstall: transformers\n",
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" Found existing installation: transformers 4.35.2\n",
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" Uninstalling transformers-4.35.2:\n",
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" Successfully uninstalled transformers-4.35.2\n",
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"Successfully installed transformers-4.36.0.dev0\n"
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]
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}
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],
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"source": [
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"!pip install git+https://github.com/huggingface/transformers"
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"cell_type": "code",
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"source": [
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"!pip install datasets"
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"colab": {
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"base_uri": "https://localhost:8080/"
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"id": "VKgybrUswa1q",
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"outputId": "5c5b315c-6a81-4ce8-e1a8-43f78c084fdc"
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"execution_count": 2,
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"outputs": [
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Collecting datasets\n",
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"Installing collected packages: pyarrow-hotfix, dill, multiprocess, datasets\n",
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"Successfully installed datasets-2.15.0 dill-0.3.7 multiprocess-0.70.15 pyarrow-hotfix-0.6\n"
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"colab": {
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"Collecting accelerate\n",
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"Installing collected packages: responses, evaluate\n",
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"Successfully installed evaluate-0.4.1 responses-0.18.0\n"
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{
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"source": [
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"!wget https://raw.githubusercontent.com/huggingface/transformers/main/examples/pytorch/question-answering/run_qa.py\n",
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"!wget https://raw.githubusercontent.com/huggingface/transformers/main/examples/pytorch/question-answering/trainer_qa.py\n",
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"!wget https://raw.githubusercontent.com/huggingface/transformers/main/examples/pytorch/question-answering/utils_qa.py"
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],
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"--2023-12-09 12:05:19-- https://raw.githubusercontent.com/huggingface/transformers/main/examples/pytorch/question-answering/run_qa.py\n",
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{
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"source": [
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+
"!ls"
|
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+
],
|
| 316 |
+
"metadata": {
|
| 317 |
+
"colab": {
|
| 318 |
+
"base_uri": "https://localhost:8080/"
|
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+
},
|
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+
"id": "Loa6y9XqzXJ4",
|
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+
"outputId": "8bd0088d-b009-4d08-c2a7-dd123598432a"
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+
},
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+
"execution_count": 6,
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+
"outputs": [
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+
{
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+
"output_type": "stream",
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+
"name": "stdout",
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+
"text": [
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+
"run_qa.py sample_data\ttrainer_qa.py utils_qa.py\n"
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+
]
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+
}
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]
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+
{
|
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+
"cell_type": "code",
|
| 336 |
+
"source": [
|
| 337 |
+
"!mkdir eval_results"
|
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+
],
|
| 339 |
+
"metadata": {
|
| 340 |
+
"id": "QDNxV31P0reW"
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+
},
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+
"execution_count": 7,
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"outputs": []
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+
},
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+
{
|
| 346 |
+
"cell_type": "code",
|
| 347 |
+
"source": [
|
| 348 |
+
"!python -m run_qa --model_name_or_path osiria/bert-italian-uncased-question-answering --dataset_name squad_it --do_predict --per_device_eval_batch_size=5 --output_dir eval_results"
|
| 349 |
+
],
|
| 350 |
+
"metadata": {
|
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+
"colab": {
|
| 352 |
+
"base_uri": "https://localhost:8080/"
|
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+
},
|
| 354 |
+
"id": "B5O5Lom8x_c4",
|
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+
"outputId": "8d066e37-8407-4232-de44-6290495776f9"
|
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+
},
|
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+
"execution_count": 8,
|
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+
"outputs": [
|
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+
{
|
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+
"output_type": "stream",
|
| 361 |
+
"name": "stdout",
|
| 362 |
+
"text": [
|
| 363 |
+
"2023-12-09 12:05:29.016992: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
|
| 364 |
+
"2023-12-09 12:05:29.017054: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
|
| 365 |
+
"2023-12-09 12:05:29.017091: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
|
| 366 |
+
"2023-12-09 12:05:30.116878: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
|
| 367 |
+
"12/09/2023 12:05:33 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False\n",
|
| 368 |
+
"12/09/2023 12:05:33 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n",
|
| 369 |
+
"_n_gpu=1,\n",
|
| 370 |
+
"adafactor=False,\n",
|
| 371 |
+
"adam_beta1=0.9,\n",
|
| 372 |
+
"adam_beta2=0.999,\n",
|
| 373 |
+
"adam_epsilon=1e-08,\n",
|
| 374 |
+
"auto_find_batch_size=False,\n",
|
| 375 |
+
"bf16=False,\n",
|
| 376 |
+
"bf16_full_eval=False,\n",
|
| 377 |
+
"data_seed=None,\n",
|
| 378 |
+
"dataloader_drop_last=False,\n",
|
| 379 |
+
"dataloader_num_workers=0,\n",
|
| 380 |
+
"dataloader_persistent_workers=False,\n",
|
| 381 |
+
"dataloader_pin_memory=True,\n",
|
| 382 |
+
"ddp_backend=None,\n",
|
| 383 |
+
"ddp_broadcast_buffers=None,\n",
|
| 384 |
+
"ddp_bucket_cap_mb=None,\n",
|
| 385 |
+
"ddp_find_unused_parameters=None,\n",
|
| 386 |
+
"ddp_timeout=1800,\n",
|
| 387 |
+
"debug=[],\n",
|
| 388 |
+
"deepspeed=None,\n",
|
| 389 |
+
"disable_tqdm=False,\n",
|
| 390 |
+
"dispatch_batches=None,\n",
|
| 391 |
+
"do_eval=False,\n",
|
| 392 |
+
"do_predict=True,\n",
|
| 393 |
+
"do_train=False,\n",
|
| 394 |
+
"eval_accumulation_steps=None,\n",
|
| 395 |
+
"eval_delay=0,\n",
|
| 396 |
+
"eval_steps=None,\n",
|
| 397 |
+
"evaluation_strategy=no,\n",
|
| 398 |
+
"fp16=False,\n",
|
| 399 |
+
"fp16_backend=auto,\n",
|
| 400 |
+
"fp16_full_eval=False,\n",
|
| 401 |
+
"fp16_opt_level=O1,\n",
|
| 402 |
+
"fsdp=[],\n",
|
| 403 |
+
"fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},\n",
|
| 404 |
+
"fsdp_min_num_params=0,\n",
|
| 405 |
+
"fsdp_transformer_layer_cls_to_wrap=None,\n",
|
| 406 |
+
"full_determinism=False,\n",
|
| 407 |
+
"gradient_accumulation_steps=1,\n",
|
| 408 |
+
"gradient_checkpointing=False,\n",
|
| 409 |
+
"gradient_checkpointing_kwargs=None,\n",
|
| 410 |
+
"greater_is_better=None,\n",
|
| 411 |
+
"group_by_length=False,\n",
|
| 412 |
+
"half_precision_backend=auto,\n",
|
| 413 |
+
"hub_always_push=False,\n",
|
| 414 |
+
"hub_model_id=None,\n",
|
| 415 |
+
"hub_private_repo=False,\n",
|
| 416 |
+
"hub_strategy=every_save,\n",
|
| 417 |
+
"hub_token=<HUB_TOKEN>,\n",
|
| 418 |
+
"ignore_data_skip=False,\n",
|
| 419 |
+
"include_inputs_for_metrics=False,\n",
|
| 420 |
+
"include_num_input_tokens_seen=False,\n",
|
| 421 |
+
"include_tokens_per_second=False,\n",
|
| 422 |
+
"jit_mode_eval=False,\n",
|
| 423 |
+
"label_names=None,\n",
|
| 424 |
+
"label_smoothing_factor=0.0,\n",
|
| 425 |
+
"learning_rate=5e-05,\n",
|
| 426 |
+
"length_column_name=length,\n",
|
| 427 |
+
"load_best_model_at_end=False,\n",
|
| 428 |
+
"local_rank=0,\n",
|
| 429 |
+
"log_level=passive,\n",
|
| 430 |
+
"log_level_replica=warning,\n",
|
| 431 |
+
"log_on_each_node=True,\n",
|
| 432 |
+
"logging_dir=eval_results/runs/Dec09_12-05-33_4da00120f505,\n",
|
| 433 |
+
"logging_first_step=False,\n",
|
| 434 |
+
"logging_nan_inf_filter=True,\n",
|
| 435 |
+
"logging_steps=500,\n",
|
| 436 |
+
"logging_strategy=steps,\n",
|
| 437 |
+
"lr_scheduler_kwargs={},\n",
|
| 438 |
+
"lr_scheduler_type=linear,\n",
|
| 439 |
+
"max_grad_norm=1.0,\n",
|
| 440 |
+
"max_steps=-1,\n",
|
| 441 |
+
"metric_for_best_model=None,\n",
|
| 442 |
+
"mp_parameters=,\n",
|
| 443 |
+
"neftune_noise_alpha=None,\n",
|
| 444 |
+
"no_cuda=False,\n",
|
| 445 |
+
"num_train_epochs=3.0,\n",
|
| 446 |
+
"optim=adamw_torch,\n",
|
| 447 |
+
"optim_args=None,\n",
|
| 448 |
+
"output_dir=eval_results,\n",
|
| 449 |
+
"overwrite_output_dir=False,\n",
|
| 450 |
+
"past_index=-1,\n",
|
| 451 |
+
"per_device_eval_batch_size=5,\n",
|
| 452 |
+
"per_device_train_batch_size=8,\n",
|
| 453 |
+
"prediction_loss_only=False,\n",
|
| 454 |
+
"push_to_hub=False,\n",
|
| 455 |
+
"push_to_hub_model_id=None,\n",
|
| 456 |
+
"push_to_hub_organization=None,\n",
|
| 457 |
+
"push_to_hub_token=<PUSH_TO_HUB_TOKEN>,\n",
|
| 458 |
+
"ray_scope=last,\n",
|
| 459 |
+
"remove_unused_columns=True,\n",
|
| 460 |
+
"report_to=['tensorboard'],\n",
|
| 461 |
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"resume_from_checkpoint=None,\n",
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| 462 |
+
"run_name=eval_results,\n",
|
| 463 |
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"save_on_each_node=False,\n",
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| 464 |
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"save_only_model=False,\n",
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| 465 |
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"save_safetensors=True,\n",
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| 466 |
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"save_steps=500,\n",
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| 467 |
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"save_strategy=steps,\n",
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| 468 |
+
"save_total_limit=None,\n",
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| 469 |
+
"seed=42,\n",
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| 470 |
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"skip_memory_metrics=True,\n",
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| 471 |
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"split_batches=False,\n",
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"tf32=None,\n",
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"torch_compile=False,\n",
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"torch_compile_backend=None,\n",
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"torchdynamo=None,\n",
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"tpu_metrics_debug=False,\n",
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"tpu_num_cores=None,\n",
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"use_cpu=False,\n",
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"use_ipex=False,\n",
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"use_legacy_prediction_loop=False,\n",
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"use_mps_device=False,\n",
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"warmup_ratio=0.0,\n",
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"warmup_steps=0,\n",
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"weight_decay=0.0,\n",
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| 486 |
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")\n",
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"https://huggingface.co/datasets/squad_it/resolve/main/squad_it.py not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/2f7a246f661e6acb3a9ad072ed14241ea343265e7d863b88717897941c3ab1dd.671c3c3daf2f05e0355b498b0f5a7f2167fa94dc6de36195fe1ba0503e6dcc30.py.incomplete\n",
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"12/09/2023 12:05:33 - INFO - datasets.utils.file_utils - https://huggingface.co/datasets/squad_it/resolve/main/squad_it.py not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/2f7a246f661e6acb3a9ad072ed14241ea343265e7d863b88717897941c3ab1dd.671c3c3daf2f05e0355b498b0f5a7f2167fa94dc6de36195fe1ba0503e6dcc30.py.incomplete\n",
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"Downloading builder script: 100% 4.74k/4.74k [00:00<00:00, 21.2MB/s]\n",
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"storing https://huggingface.co/datasets/squad_it/resolve/main/squad_it.py in cache at /root/.cache/huggingface/datasets/downloads/2f7a246f661e6acb3a9ad072ed14241ea343265e7d863b88717897941c3ab1dd.671c3c3daf2f05e0355b498b0f5a7f2167fa94dc6de36195fe1ba0503e6dcc30.py\n",
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"12/09/2023 12:05:34 - INFO - datasets.utils.file_utils - storing https://huggingface.co/datasets/squad_it/resolve/main/squad_it.py in cache at /root/.cache/huggingface/datasets/downloads/2f7a246f661e6acb3a9ad072ed14241ea343265e7d863b88717897941c3ab1dd.671c3c3daf2f05e0355b498b0f5a7f2167fa94dc6de36195fe1ba0503e6dcc30.py\n",
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"12/09/2023 12:05:34 - INFO - datasets.utils.file_utils - creating metadata file for /root/.cache/huggingface/datasets/downloads/2f7a246f661e6acb3a9ad072ed14241ea343265e7d863b88717897941c3ab1dd.671c3c3daf2f05e0355b498b0f5a7f2167fa94dc6de36195fe1ba0503e6dcc30.py\n",
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"12/09/2023 12:05:34 - INFO - datasets.utils.file_utils - https://huggingface.co/datasets/squad_it/resolve/main/dataset_infos.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/f6d7650a1e4a9f0e42b54f34ac614f7c1142ad26c1bd19a448eb606fe09f7515.b459489a7b1a4d859decbeef851034c7846ef6cce8ec2cf192cf4b4f40d0865d.incomplete\n",
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"storing https://huggingface.co/datasets/squad_it/resolve/main/dataset_infos.json in cache at /root/.cache/huggingface/datasets/downloads/f6d7650a1e4a9f0e42b54f34ac614f7c1142ad26c1bd19a448eb606fe09f7515.b459489a7b1a4d859decbeef851034c7846ef6cce8ec2cf192cf4b4f40d0865d\n",
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"12/09/2023 12:05:34 - INFO - datasets.utils.file_utils - storing https://huggingface.co/datasets/squad_it/resolve/main/dataset_infos.json in cache at /root/.cache/huggingface/datasets/downloads/f6d7650a1e4a9f0e42b54f34ac614f7c1142ad26c1bd19a448eb606fe09f7515.b459489a7b1a4d859decbeef851034c7846ef6cce8ec2cf192cf4b4f40d0865d\n",
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"creating metadata file for /root/.cache/huggingface/datasets/downloads/f6d7650a1e4a9f0e42b54f34ac614f7c1142ad26c1bd19a448eb606fe09f7515.b459489a7b1a4d859decbeef851034c7846ef6cce8ec2cf192cf4b4f40d0865d\n",
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"12/09/2023 12:05:34 - INFO - datasets.utils.file_utils - creating metadata file for /root/.cache/huggingface/datasets/downloads/f6d7650a1e4a9f0e42b54f34ac614f7c1142ad26c1bd19a448eb606fe09f7515.b459489a7b1a4d859decbeef851034c7846ef6cce8ec2cf192cf4b4f40d0865d\n",
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"https://huggingface.co/datasets/squad_it/resolve/main/README.md not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb.incomplete\n",
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"12/09/2023 12:05:35 - INFO - datasets.utils.file_utils - https://huggingface.co/datasets/squad_it/resolve/main/README.md not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb.incomplete\n",
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"Downloading readme: 100% 7.27k/7.27k [00:00<00:00, 26.1MB/s]\n",
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+
"storing https://huggingface.co/datasets/squad_it/resolve/main/README.md in cache at /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb\n",
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+
"12/09/2023 12:05:35 - INFO - datasets.utils.file_utils - storing https://huggingface.co/datasets/squad_it/resolve/main/README.md in cache at /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb\n",
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"creating metadata file for /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb\n",
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"12/09/2023 12:05:35 - INFO - datasets.utils.file_utils - creating metadata file for /root/.cache/huggingface/datasets/downloads/b664892e5965a1ef2e173eadc7e9cbf6ad4aeb6240d7b3bb6ab9f32850363a6f.71fe7dbf5f3b574d85b57b5a722ebc49fe8ec8b03d655344891fb1b05c4634fb\n",
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+
"Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/squad_it/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71\n",
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+
"12/09/2023 12:05:35 - INFO - datasets.info - Loading Dataset Infos from /root/.cache/huggingface/modules/datasets_modules/datasets/squad_it/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71\n",
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+
"Generating dataset squad_it (/root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71)\n",
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+
"12/09/2023 12:05:35 - INFO - datasets.builder - Generating dataset squad_it (/root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71)\n",
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+
"Downloading and preparing dataset squad_it/default to /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71...\n",
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+
"12/09/2023 12:05:35 - INFO - datasets.builder - Downloading and preparing dataset squad_it/default to /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71...\n",
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+
"Dataset not on Hf google storage. Downloading and preparing it from source\n",
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"12/09/2023 12:05:35 - INFO - datasets.builder - Dataset not on Hf google storage. Downloading and preparing it from source\n",
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"Downloading data files: 0% 0/2 [00:00<?, ?it/s]https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b.incomplete\n",
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+
"12/09/2023 12:05:36 - INFO - datasets.utils.file_utils - https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b.incomplete\n",
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"Downloading data: 0% 0.00/7.73M [00:00<?, ?B/s]\u001b[A\n",
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"Downloading data: 100% 7.73M/7.73M [00:00<00:00, 55.1MB/s]\n",
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+
"storing https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz in cache at /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b\n",
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| 522 |
+
"12/09/2023 12:05:36 - INFO - datasets.utils.file_utils - storing https://github.com/crux82/squad-it/raw/master/SQuAD_it-train.json.gz in cache at /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b\n",
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"creating metadata file for /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b\n",
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"12/09/2023 12:05:36 - INFO - datasets.utils.file_utils - creating metadata file for /root/.cache/huggingface/datasets/downloads/44ac0548c3284061d1356ff7f5212fe42b923b0aa0854c886ce93dfeb7ab629b\n",
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"Downloading data files: 50% 1/2 [00:01<00:01, 1.19s/it]https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f.incomplete\n",
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+
"12/09/2023 12:05:37 - INFO - datasets.utils.file_utils - https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f.incomplete\n",
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+
"storing https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz in cache at /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f\n",
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+
"12/09/2023 12:05:37 - INFO - datasets.utils.file_utils - storing https://github.com/crux82/squad-it/raw/master/SQuAD_it-test.json.gz in cache at /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f\n",
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+
"creating metadata file for /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f\n",
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| 532 |
+
"12/09/2023 12:05:37 - INFO - datasets.utils.file_utils - creating metadata file for /root/.cache/huggingface/datasets/downloads/e560a4a54eb929ce542e945627942afca80859dcbf499866a59984eb9026d31f\n",
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+
"Downloading took 0.0 min\n",
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"12/09/2023 12:05:37 - INFO - datasets.download.download_manager - Downloading took 0.0 min\n",
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+
"Checksum Computation took 0.0 min\n",
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"12/09/2023 12:05:37 - INFO - datasets.download.download_manager - Checksum Computation took 0.0 min\n",
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"Generating train split\n",
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"12/09/2023 12:05:38 - INFO - datasets.builder - Generating train split\n",
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"Generating train split: 100% 54159/54159 [00:06<00:00, 8803.51 examples/s] \n",
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"Generating test split\n",
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+
"12/09/2023 12:05:44 - INFO - datasets.builder - Generating test split\n",
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"Generating test split: 100% 7609/7609 [00:00<00:00, 11069.99 examples/s]\n",
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+
"All the splits matched successfully.\n",
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+
"12/09/2023 12:05:44 - INFO - datasets.utils.info_utils - All the splits matched successfully.\n",
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| 547 |
+
"Dataset squad_it downloaded and prepared to /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71. Subsequent calls will reuse this data.\n",
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+
"12/09/2023 12:05:44 - INFO - datasets.builder - Dataset squad_it downloaded and prepared to /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71. Subsequent calls will reuse this data.\n",
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"[INFO|configuration_utils.py:739] 2023-12-09 12:05:45,154 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--osiria--bert-italian-uncased-question-answering/snapshots/9985f20cde546f78a743c4d4f1efd605519b1c41/config.json\n",
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+
"[INFO|configuration_utils.py:802] 2023-12-09 12:05:45,159 >> Model config BertConfig {\n",
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| 552 |
+
" \"_name_or_path\": \"osiria/bert-italian-uncased-question-answering\",\n",
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+
" \"architectures\": [\n",
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+
" \"BertForQuestionAnswering\"\n",
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" ],\n",
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+
" \"attention_probs_dropout_prob\": 0.1,\n",
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+
" \"classifier_dropout\": null,\n",
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+
" \"directionality\": \"bidi\",\n",
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+
" \"hidden_act\": \"gelu\",\n",
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+
" \"hidden_dropout_prob\": 0.1,\n",
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" \"hidden_size\": 768,\n",
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" \"initializer_range\": 0.02,\n",
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" \"intermediate_size\": 3072,\n",
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" \"layer_norm_eps\": 1e-12,\n",
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" \"max_position_embeddings\": 512,\n",
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" \"model_type\": \"bert\",\n",
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+
" \"num_attention_heads\": 12,\n",
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+
" \"num_hidden_layers\": 12,\n",
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+
" \"pad_token_id\": 0,\n",
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+
" \"pooler_fc_size\": 768,\n",
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" \"pooler_num_attention_heads\": 12,\n",
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" \"pooler_num_fc_layers\": 3,\n",
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" \"pooler_size_per_head\": 128,\n",
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+
" \"pooler_type\": \"first_token_transform\",\n",
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" \"position_embedding_type\": \"absolute\",\n",
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+
" \"torch_dtype\": \"float32\",\n",
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+
" \"transformers_version\": \"4.36.0.dev0\",\n",
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+
" \"type_vocab_size\": 2,\n",
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" \"use_cache\": true,\n",
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+
" \"vocab_size\": 30154\n",
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"}\n",
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+
"[INFO|tokenization_utils_base.py:2026] 2023-12-09 12:05:45,575 >> loading file vocab.txt from cache at /root/.cache/huggingface/hub/models--osiria--bert-italian-uncased-question-answering/snapshots/9985f20cde546f78a743c4d4f1efd605519b1c41/vocab.txt\n",
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"[INFO|tokenization_utils_base.py:2026] 2023-12-09 12:05:45,575 >> loading file tokenizer.json from cache at None\n",
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+
"[INFO|tokenization_utils_base.py:2026] 2023-12-09 12:05:45,575 >> loading file added_tokens.json from cache at None\n",
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"[INFO|tokenization_utils_base.py:2026] 2023-12-09 12:05:45,575 >> loading file special_tokens_map.json from cache at None\n",
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"[INFO|tokenization_utils_base.py:2026] 2023-12-09 12:05:45,575 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--osiria--bert-italian-uncased-question-answering/snapshots/9985f20cde546f78a743c4d4f1efd605519b1c41/tokenizer_config.json\n",
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"pytorch_model.bin: 100% 435M/435M [00:09<00:00, 46.2MB/s]\n",
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"[INFO|modeling_utils.py:3299] 2023-12-09 12:05:55,532 >> loading weights file pytorch_model.bin from cache at /root/.cache/huggingface/hub/models--osiria--bert-italian-uncased-question-answering/snapshots/9985f20cde546f78a743c4d4f1efd605519b1c41/pytorch_model.bin\n",
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"[INFO|modeling_utils.py:4139] 2023-12-09 12:05:56,828 >> All model checkpoint weights were used when initializing BertForQuestionAnswering.\n",
|
| 593 |
+
"\n",
|
| 594 |
+
"[INFO|modeling_utils.py:4147] 2023-12-09 12:05:56,828 >> All the weights of BertForQuestionAnswering were initialized from the model checkpoint at osiria/bert-italian-uncased-question-answering.\n",
|
| 595 |
+
"If your task is similar to the task the model of the checkpoint was trained on, you can already use BertForQuestionAnswering for predictions without further training.\n",
|
| 596 |
+
"Running tokenizer on prediction dataset: 0% 0/7609 [00:00<?, ? examples/s]Caching processed dataset at /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71/cache-6925a2ff4566b537.arrow\n",
|
| 597 |
+
"12/09/2023 12:05:57 - INFO - datasets.arrow_dataset - Caching processed dataset at /root/.cache/huggingface/datasets/squad_it/default/0.1.0/d442bdb4794b4bae227ab19105b76d706ed7cf2ac342e4c9da4a5c36bde19d71/cache-6925a2ff4566b537.arrow\n",
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"Running tokenizer on prediction dataset: 100% 7609/7609 [00:06<00:00, 1097.66 examples/s]\n",
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"Downloading builder script: 100% 4.53k/4.53k [00:00<00:00, 13.1MB/s]\n",
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"Downloading extra modules: 100% 3.32k/3.32k [00:00<00:00, 12.0MB/s]\n",
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"12/09/2023 12:06:10 - INFO - __main__ - *** Predict ***\n",
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| 602 |
+
"[INFO|trainer.py:712] 2023-12-09 12:06:10,618 >> The following columns in the test set don't have a corresponding argument in `BertForQuestionAnswering.forward` and have been ignored: example_id, offset_mapping. If example_id, offset_mapping are not expected by `BertForQuestionAnswering.forward`, you can safely ignore this message.\n",
|
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"[INFO|trainer.py:3154] 2023-12-09 12:06:10,622 >> ***** Running Prediction *****\n",
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"[INFO|trainer.py:3156] 2023-12-09 12:06:10,622 >> Num examples = 7942\n",
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"[INFO|trainer.py:3159] 2023-12-09 12:06:10,622 >> Batch size = 5\n",
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"100% 7609/7609 [00:27<00:00, 281.02it/s]\n",
|
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+
"12/09/2023 12:10:11 - INFO - utils_qa - Saving predictions to eval_results/predict_predictions.json.\n",
|
| 860 |
+
"12/09/2023 12:10:11 - INFO - utils_qa - Saving nbest_preds to eval_results/predict_nbest_predictions.json.\n",
|
| 861 |
+
"***** predict metrics *****\n",
|
| 862 |
+
" predict_samples = 7942\n",
|
| 863 |
+
" test_exact_match = 65.6065\n",
|
| 864 |
+
" test_f1 = 77.1676\n",
|
| 865 |
+
" test_runtime = 0:03:24.92\n",
|
| 866 |
+
" test_samples_per_second = 38.757\n",
|
| 867 |
+
" test_steps_per_second = 7.754\n",
|
| 868 |
+
"[INFO|modelcard.py:452] 2023-12-09 12:10:15,872 >> Dropping the following result as it does not have all the necessary fields:\n",
|
| 869 |
+
"{'task': {'name': 'Question Answering', 'type': 'question-answering'}, 'dataset': {'name': 'squad_it', 'type': 'squad_it'}}\n",
|
| 870 |
+
"100% 1589/1589 [04:02<00:00, 6.56it/s]\n"
|
| 871 |
+
]
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| 872 |
+
}
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| 873 |
+
]
|
| 874 |
+
},
|
| 875 |
+
{
|
| 876 |
+
"cell_type": "code",
|
| 877 |
+
"source": [],
|
| 878 |
+
"metadata": {
|
| 879 |
+
"id": "rMyhUFpnItIQ"
|
| 880 |
+
},
|
| 881 |
+
"execution_count": null,
|
| 882 |
+
"outputs": []
|
| 883 |
+
}
|
| 884 |
+
]
|
| 885 |
+
}
|