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2024-09-05 21:40:16.805233: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. |
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2024-09-05 21:40:16.823412: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered |
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2024-09-05 21:40:16.844949: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered |
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2024-09-05 21:40:16.851514: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered |
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2024-09-05 21:40:16.867297: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. |
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To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. |
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2024-09-05 21:40:18.144744: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT |
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/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of π€ Transformers. Use `eval_strategy` instead |
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warnings.warn( |
|
09/05/2024 21:40:20 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: False |
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09/05/2024 21:40:20 - INFO - __main__ - Training/evaluation parameters TrainingArguments( |
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_n_gpu=1, |
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accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False}, |
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adafactor=False, |
|
adam_beta1=0.9, |
|
adam_beta2=0.999, |
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adam_epsilon=1e-08, |
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auto_find_batch_size=False, |
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batch_eval_metrics=False, |
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bf16=False, |
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bf16_full_eval=False, |
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data_seed=None, |
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dataloader_drop_last=False, |
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dataloader_num_workers=0, |
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dataloader_persistent_workers=False, |
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dataloader_pin_memory=True, |
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dataloader_prefetch_factor=None, |
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ddp_backend=None, |
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ddp_broadcast_buffers=None, |
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ddp_bucket_cap_mb=None, |
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ddp_find_unused_parameters=None, |
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ddp_timeout=1800, |
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debug=[], |
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deepspeed=None, |
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disable_tqdm=False, |
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dispatch_batches=None, |
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do_eval=True, |
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do_predict=True, |
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do_train=True, |
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eval_accumulation_steps=None, |
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eval_delay=0, |
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eval_do_concat_batches=True, |
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eval_on_start=False, |
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eval_steps=None, |
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eval_strategy=epoch, |
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eval_use_gather_object=False, |
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evaluation_strategy=epoch, |
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fp16=False, |
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fp16_backend=auto, |
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fp16_full_eval=False, |
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fp16_opt_level=O1, |
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fsdp=[], |
|
fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, |
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fsdp_min_num_params=0, |
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fsdp_transformer_layer_cls_to_wrap=None, |
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full_determinism=False, |
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gradient_accumulation_steps=2, |
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gradient_checkpointing=False, |
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gradient_checkpointing_kwargs=None, |
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greater_is_better=True, |
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group_by_length=False, |
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half_precision_backend=auto, |
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hub_always_push=False, |
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hub_model_id=None, |
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hub_private_repo=False, |
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hub_strategy=every_save, |
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hub_token=<HUB_TOKEN>, |
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ignore_data_skip=False, |
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include_inputs_for_metrics=False, |
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include_num_input_tokens_seen=False, |
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include_tokens_per_second=False, |
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jit_mode_eval=False, |
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label_names=None, |
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label_smoothing_factor=0.0, |
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learning_rate=5e-05, |
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length_column_name=length, |
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load_best_model_at_end=True, |
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local_rank=0, |
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log_level=passive, |
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log_level_replica=warning, |
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log_on_each_node=True, |
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logging_dir=/content/dissertation/scripts/ner/output/tb, |
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logging_first_step=False, |
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logging_nan_inf_filter=True, |
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logging_steps=500, |
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logging_strategy=steps, |
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lr_scheduler_kwargs={}, |
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lr_scheduler_type=linear, |
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max_grad_norm=1.0, |
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max_steps=-1, |
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metric_for_best_model=f1, |
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mp_parameters=, |
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neftune_noise_alpha=None, |
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no_cuda=False, |
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num_train_epochs=10.0, |
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optim=adamw_torch, |
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optim_args=None, |
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optim_target_modules=None, |
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output_dir=/content/dissertation/scripts/ner/output, |
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overwrite_output_dir=True, |
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past_index=-1, |
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per_device_eval_batch_size=8, |
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per_device_train_batch_size=32, |
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prediction_loss_only=False, |
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push_to_hub=True, |
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push_to_hub_model_id=None, |
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push_to_hub_organization=None, |
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push_to_hub_token=<PUSH_TO_HUB_TOKEN>, |
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ray_scope=last, |
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remove_unused_columns=True, |
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report_to=['tensorboard'], |
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restore_callback_states_from_checkpoint=False, |
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resume_from_checkpoint=None, |
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run_name=/content/dissertation/scripts/ner/output, |
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save_on_each_node=False, |
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save_only_model=False, |
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save_safetensors=True, |
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save_steps=500, |
|
save_strategy=epoch, |
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save_total_limit=None, |
|
seed=42, |
|
skip_memory_metrics=True, |
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split_batches=None, |
|
tf32=None, |
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torch_compile=False, |
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torch_compile_backend=None, |
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torch_compile_mode=None, |
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torch_empty_cache_steps=None, |
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torchdynamo=None, |
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tpu_metrics_debug=False, |
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tpu_num_cores=None, |
|
use_cpu=False, |
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use_ipex=False, |
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use_legacy_prediction_loop=False, |
|
use_mps_device=False, |
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warmup_ratio=0.0, |
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warmup_steps=0, |
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weight_decay=0.0, |
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) |
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[INFO|configuration_utils.py:733] 2024-09-05 21:40:33,477 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/config.json |
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[INFO|configuration_utils.py:800] 2024-09-05 21:40:33,486 >> Model config RobertaConfig { |
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"_name_or_path": "PlanTL-GOB-ES/bsc-bio-ehr-es", |
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"architectures": [ |
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"RobertaForMaskedLM" |
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], |
|
"attention_probs_dropout_prob": 0.1, |
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"bos_token_id": 0, |
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"classifier_dropout": null, |
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"eos_token_id": 2, |
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"finetuning_task": "ner", |
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"gradient_checkpointing": false, |
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"hidden_act": "gelu", |
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"hidden_dropout_prob": 0.1, |
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"hidden_size": 768, |
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"id2label": { |
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"0": "O", |
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"1": "B-MORFOLOGIA_NEOPLASIA", |
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"2": "I-MORFOLOGIA_NEOPLASIA" |
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}, |
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"initializer_range": 0.02, |
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"intermediate_size": 3072, |
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"label2id": { |
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"B-MORFOLOGIA_NEOPLASIA": 1, |
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"I-MORFOLOGIA_NEOPLASIA": 2, |
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"O": 0 |
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}, |
|
"layer_norm_eps": 1e-05, |
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"max_position_embeddings": 514, |
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"model_type": "roberta", |
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"num_attention_heads": 12, |
|
"num_hidden_layers": 12, |
|
"pad_token_id": 1, |
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"position_embedding_type": "absolute", |
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"transformers_version": "4.44.2", |
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"type_vocab_size": 1, |
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"use_cache": true, |
|
"vocab_size": 50262 |
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} |
|
|
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[INFO|configuration_utils.py:733] 2024-09-05 21:40:33,679 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/config.json |
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[INFO|configuration_utils.py:800] 2024-09-05 21:40:33,680 >> Model config RobertaConfig { |
|
"_name_or_path": "PlanTL-GOB-ES/bsc-bio-ehr-es", |
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"architectures": [ |
|
"RobertaForMaskedLM" |
|
], |
|
"attention_probs_dropout_prob": 0.1, |
|
"bos_token_id": 0, |
|
"classifier_dropout": null, |
|
"eos_token_id": 2, |
|
"gradient_checkpointing": false, |
|
"hidden_act": "gelu", |
|
"hidden_dropout_prob": 0.1, |
|
"hidden_size": 768, |
|
"initializer_range": 0.02, |
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"intermediate_size": 3072, |
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"layer_norm_eps": 1e-05, |
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"max_position_embeddings": 514, |
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"model_type": "roberta", |
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"num_attention_heads": 12, |
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"num_hidden_layers": 12, |
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"pad_token_id": 1, |
|
"position_embedding_type": "absolute", |
|
"transformers_version": "4.44.2", |
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"type_vocab_size": 1, |
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"use_cache": true, |
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"vocab_size": 50262 |
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} |
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|
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file vocab.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/vocab.json |
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file merges.txt from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/merges.txt |
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file tokenizer.json from cache at None |
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file added_tokens.json from cache at None |
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/special_tokens_map.json |
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[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,108 >> loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/tokenizer_config.json |
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[INFO|configuration_utils.py:733] 2024-09-05 21:40:35,108 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/config.json |
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[INFO|configuration_utils.py:800] 2024-09-05 21:40:35,109 >> Model config RobertaConfig { |
|
"_name_or_path": "PlanTL-GOB-ES/bsc-bio-ehr-es", |
|
"architectures": [ |
|
"RobertaForMaskedLM" |
|
], |
|
"attention_probs_dropout_prob": 0.1, |
|
"bos_token_id": 0, |
|
"classifier_dropout": null, |
|
"eos_token_id": 2, |
|
"gradient_checkpointing": false, |
|
"hidden_act": "gelu", |
|
"hidden_dropout_prob": 0.1, |
|
"hidden_size": 768, |
|
"initializer_range": 0.02, |
|
"intermediate_size": 3072, |
|
"layer_norm_eps": 1e-05, |
|
"max_position_embeddings": 514, |
|
"model_type": "roberta", |
|
"num_attention_heads": 12, |
|
"num_hidden_layers": 12, |
|
"pad_token_id": 1, |
|
"position_embedding_type": "absolute", |
|
"transformers_version": "4.44.2", |
|
"type_vocab_size": 1, |
|
"use_cache": true, |
|
"vocab_size": 50262 |
|
} |
|
|
|
/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884 |
|
warnings.warn( |
|
[INFO|configuration_utils.py:733] 2024-09-05 21:40:35,189 >> loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/config.json |
|
[INFO|configuration_utils.py:800] 2024-09-05 21:40:35,190 >> Model config RobertaConfig { |
|
"_name_or_path": "PlanTL-GOB-ES/bsc-bio-ehr-es", |
|
"architectures": [ |
|
"RobertaForMaskedLM" |
|
], |
|
"attention_probs_dropout_prob": 0.1, |
|
"bos_token_id": 0, |
|
"classifier_dropout": null, |
|
"eos_token_id": 2, |
|
"gradient_checkpointing": false, |
|
"hidden_act": "gelu", |
|
"hidden_dropout_prob": 0.1, |
|
"hidden_size": 768, |
|
"initializer_range": 0.02, |
|
"intermediate_size": 3072, |
|
"layer_norm_eps": 1e-05, |
|
"max_position_embeddings": 514, |
|
"model_type": "roberta", |
|
"num_attention_heads": 12, |
|
"num_hidden_layers": 12, |
|
"pad_token_id": 1, |
|
"position_embedding_type": "absolute", |
|
"transformers_version": "4.44.2", |
|
"type_vocab_size": 1, |
|
"use_cache": true, |
|
"vocab_size": 50262 |
|
} |
|
|
|
[INFO|modeling_utils.py:3678] 2024-09-05 21:40:52,003 >> loading weights file pytorch_model.bin from cache at /root/.cache/huggingface/hub/models--PlanTL-GOB-ES--bsc-bio-ehr-es/snapshots/1e543adb2d21f19d85a89305eebdbd64ab656b99/pytorch_model.bin |
|
[INFO|modeling_utils.py:4497] 2024-09-05 21:40:52,139 >> Some weights of the model checkpoint at PlanTL-GOB-ES/bsc-bio-ehr-es were not used when initializing RobertaForTokenClassification: ['lm_head.bias', 'lm_head.decoder.bias', 'lm_head.decoder.weight', 'lm_head.dense.bias', 'lm_head.dense.weight', 'lm_head.layer_norm.bias', 'lm_head.layer_norm.weight'] |
|
- This IS expected if you are initializing RobertaForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). |
|
- This IS NOT expected if you are initializing RobertaForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). |
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[WARNING|modeling_utils.py:4509] 2024-09-05 21:40:52,139 >> Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at PlanTL-GOB-ES/bsc-bio-ehr-es and are newly initialized: ['classifier.bias', 'classifier.weight'] |
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You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference. |
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/content/dissertation/scripts/ner/run_ner_train.py:397: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library π€ Evaluate: https://huggingface.co/docs/evaluate |
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metric = load_metric("seqeval", trust_remote_code=True) |
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Downloading builder script: 6.33kB [00:00, 11.4MB/s] |
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[INFO|trainer.py:811] 2024-09-05 21:40:58,780 >> The following columns in the training set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, id, ner_tags. If tokens, id, ner_tags are not expected by `RobertaForTokenClassification.forward`, you can safely ignore this message. |
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[INFO|trainer.py:2134] 2024-09-05 21:40:59,480 >> ***** Running training ***** |
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[INFO|trainer.py:2135] 2024-09-05 21:40:59,480 >> Num examples = 32,675 |
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[INFO|trainer.py:2136] 2024-09-05 21:40:59,480 >> Num Epochs = 10 |
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[INFO|trainer.py:2137] 2024-09-05 21:40:59,480 >> Instantaneous batch size per device = 32 |
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[INFO|trainer.py:2140] 2024-09-05 21:40:59,480 >> Total train batch size (w. parallel, distributed & accumulation) = 64 |
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[INFO|trainer.py:2141] 2024-09-05 21:40:59,480 >> Gradient Accumulation steps = 2 |
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[INFO|trainer.py:2142] 2024-09-05 21:40:59,480 >> Total optimization steps = 5,110 |
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[INFO|trainer.py:2143] 2024-09-05 21:40:59,481 >> Number of trainable parameters = 124,055,043 |
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10%|β | 511/5110 [02:02<15:48, 4.85it/s][INFO|trainer.py:811] 2024-09-05 21:43:02,475 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, id, ner_tags. If tokens, id, ner_tags are not expected by `RobertaForTokenClassification.forward`, you can safely ignore this message. |
|
[INFO|trainer.py:3819] 2024-09-05 21:43:02,477 >> |
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***** Running Evaluation ***** |
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[INFO|trainer.py:3821] 2024-09-05 21:43:02,477 >> Num examples = 7354 |
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[INFO|trainer.py:3824] 2024-09-05 21:43:02,477 >> Batch size = 8 |
|
{'loss': 0.0542, 'grad_norm': 0.2284504771232605, 'learning_rate': 4.510763209393347e-05, 'epoch': 0.98} |
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10%|β | 95/920 [00:01<00:10, 77.87it/s][A |
|
11%|β | 103/920 [00:01<00:10, 78.49it/s][A |
|
12%|ββ | 111/920 [00:01<00:10, 78.11it/s][A |
|
13%|ββ | 120/920 [00:01<00:10, 78.92it/s][A |
|
14%|ββ | 128/920 [00:01<00:10, 74.71it/s][A |
|
15%|ββ | 137/920 [00:01<00:10, 77.16it/s][A |
|
16%|ββ | 146/920 [00:01<00:09, 79.00it/s][A |
|
17%|ββ | 154/920 [00:01<00:09, 79.03it/s][A |
|
18%|ββ | 163/920 [00:02<00:09, 79.61it/s][A |
|
19%|ββ | 172/920 [00:02<00:09, 81.23it/s][A |
|
20%|ββ | 181/920 [00:02<00:09, 81.86it/s][A |
|
21%|ββ | 190/920 [00:02<00:08, 82.13it/s][A |
|
22%|βββ | 199/920 [00:02<00:08, 81.55it/s][A |
|
23%|βββ | 208/920 [00:02<00:09, 77.57it/s][A |
|
24%|βββ | 217/920 [00:02<00:08, 78.97it/s][A |
|
24%|βββ | 225/920 [00:02<00:08, 79.25it/s][A |
|
25%|βββ | 234/920 [00:02<00:08, 81.15it/s][A |
|
26%|βββ | 243/920 [00:03<00:08, 82.39it/s][A |
|
27%|βββ | 252/920 [00:03<00:08, 80.82it/s][A |
|
28%|βββ | 261/920 [00:03<00:08, 79.20it/s][A |
|
29%|βββ | 269/920 [00:03<00:08, 79.24it/s][A |
|
30%|βββ | 278/920 [00:03<00:07, 80.57it/s][A |
|
31%|βββ | 287/920 [00:03<00:07, 80.61it/s][A |
|
32%|ββββ | 296/920 [00:03<00:07, 80.74it/s][A |
|
33%|ββββ | 305/920 [00:03<00:07, 80.19it/s][A |
|
34%|ββββ | 314/920 [00:03<00:07, 80.93it/s][A |
|
35%|ββββ | 323/920 [00:04<00:07, 79.78it/s][A |
|
36%|ββββ | 331/920 [00:04<00:07, 79.02it/s][A |
|
37%|ββββ | 339/920 [00:04<00:07, 76.52it/s][A |
|
38%|ββββ | 347/920 [00:04<00:07, 76.64it/s][A |
|
39%|ββββ | 355/920 [00:04<00:07, 77.24it/s][A |
|
39%|ββββ | 363/920 [00:04<00:07, 77.76it/s][A |
|
40%|ββββ | 372/920 [00:04<00:06, 78.98it/s][A |
|
41%|βββββ | 381/920 [00:04<00:06, 80.50it/s][A |
|
42%|βββββ | 390/920 [00:04<00:06, 80.32it/s][A |
|
43%|βββββ | 399/920 [00:05<00:06, 76.14it/s][A |
|
44%|βββββ | 407/920 [00:05<00:06, 74.87it/s][A |
|
45%|βββββ | 416/920 [00:05<00:06, 76.95it/s][A |
|
46%|βββββ | 425/920 [00:05<00:06, 78.23it/s][A |
|
47%|βββββ | 434/920 [00:05<00:06, 79.25it/s][A |
|
48%|βββββ | 443/920 [00:05<00:05, 80.48it/s][A |
|
49%|βββββ | 452/920 [00:05<00:05, 80.80it/s][A |
|
50%|βββββ | 461/920 [00:05<00:05, 80.93it/s][A |
|
51%|βββββ | 470/920 [00:05<00:05, 80.02it/s][A |
|
52%|ββββββ | 479/920 [00:06<00:05, 80.23it/s][A |
|
53%|ββββββ | 488/920 [00:06<00:05, 80.26it/s][A |
|
54%|ββββββ | 497/920 [00:06<00:05, 80.36it/s][A |
|
55%|ββββββ | 506/920 [00:06<00:05, 81.30it/s][A |
|
56%|ββββββ | 515/920 [00:06<00:04, 81.42it/s][A |
|
57%|ββββββ | 524/920 [00:06<00:04, 81.62it/s][A |
|
58%|ββββββ | 533/920 [00:06<00:04, 81.99it/s][A |
|
59%|ββββββ | 542/920 [00:06<00:04, 81.88it/s][A |
|
60%|ββββββ | 551/920 [00:06<00:04, 78.04it/s][A |
|
61%|ββββββ | 559/920 [00:07<00:04, 76.38it/s][A |
|
62%|βββββββ | 568/920 [00:07<00:04, 77.68it/s][A |
|
63%|βββββββ | 577/920 [00:07<00:04, 79.04it/s][A |
|
64%|βββββββ | 585/920 [00:07<00:04, 78.90it/s][A |
|
65%|βββββββ | 594/920 [00:07<00:04, 80.30it/s][A |
|
66%|βββββββ | 603/920 [00:07<00:03, 81.40it/s][A |
|
67%|βββββββ | 612/920 [00:07<00:03, 81.11it/s][A |
|
68%|βββββββ | 621/920 [00:07<00:03, 79.75it/s][A |
|
68%|βββββββ | 629/920 [00:07<00:03, 77.84it/s][A |
|
69%|βββββββ | 637/920 [00:08<00:03, 77.80it/s][A |
|
70%|βββββββ | 646/920 [00:08<00:03, 78.99it/s][A |
|
71%|βββββββ | 655/920 [00:08<00:03, 79.72it/s][A |
|
72%|ββββββββ | 664/920 [00:08<00:03, 80.67it/s][A |
|
73%|ββββββββ | 673/920 [00:08<00:03, 81.27it/s][A |
|
74%|ββββββββ | 682/920 [00:08<00:02, 82.04it/s][A |
|
75%|ββββββββ | 691/920 [00:08<00:02, 81.85it/s][A |
|
76%|ββββββββ | 700/920 [00:08<00:02, 81.24it/s][A |
|
77%|ββββββββ | 709/920 [00:08<00:02, 80.14it/s][A |
|
78%|ββββββββ | 718/920 [00:09<00:02, 80.64it/s][A |
|
79%|ββββββββ | 727/920 [00:09<00:02, 81.54it/s][A |
|
80%|ββββββββ | 736/920 [00:09<00:02, 81.40it/s][A |
|
81%|ββββββββ | 745/920 [00:09<00:02, 77.96it/s][A |
|
82%|βββββββββ | 754/920 [00:09<00:02, 79.48it/s][A |
|
83%|βββββββββ | 762/920 [00:09<00:02, 78.68it/s][A |
|
84%|βββββββββ | 771/920 [00:09<00:01, 80.44it/s][A |
|
85%|βββββββββ | 780/920 [00:09<00:01, 79.54it/s][A |
|
86%|βββββββββ | 789/920 [00:09<00:01, 80.86it/s][A |
|
87%|βββββββββ | 798/920 [00:10<00:01, 80.98it/s][A |
|
88%|βββββββββ | 807/920 [00:10<00:01, 78.75it/s][A |
|
89%|βββββββββ | 816/920 [00:10<00:01, 79.89it/s][A |
|
90%|βββββββββ | 825/920 [00:10<00:01, 81.14it/s][A |
|
91%|βββββββββ | 834/920 [00:10<00:01, 81.82it/s][A |
|
92%|ββββββββββ| 843/920 [00:10<00:00, 82.50it/s][A |
|
93%|ββββββββββ| 852/920 [00:10<00:00, 79.23it/s][A |
|
93%|ββββββββββ| 860/920 [00:10<00:00, 77.71it/s][A |
|
94%|ββββββββββ| 868/920 [00:10<00:00, 68.84it/s][A |
|
95%|ββββββββββ| 877/920 [00:11<00:00, 73.34it/s][A |
|
96%|ββββββββββ| 886/920 [00:11<00:00, 75.71it/s][A |
|
97%|ββββββββββ| 894/920 [00:11<00:00, 73.74it/s][A |
|
98%|ββββββββββ| 902/920 [00:11<00:00, 74.81it/s][A |
|
99%|ββββββββββ| 910/920 [00:11<00:00, 74.55it/s][A |
|
100%|ββββββββββ| 918/920 [00:11<00:00, 75.64it/s][A
|
|
[A
10%|β | 511/5110 [02:18<15:48, 4.85it/s] |
|
100%|ββββββββββ| 920/920 [00:15<00:00, 75.64it/s][A |
|
[A[INFO|trainer.py:3503] 2024-09-05 21:43:18,141 >> Saving model checkpoint to /content/dissertation/scripts/ner/output/checkpoint-511 |
|
[INFO|configuration_utils.py:472] 2024-09-05 21:43:18,143 >> Configuration saved in /content/dissertation/scripts/ner/output/checkpoint-511/config.json |
|
[INFO|modeling_utils.py:2799] 2024-09-05 21:43:19,170 >> Model weights saved in /content/dissertation/scripts/ner/output/checkpoint-511/model.safetensors |
|
[INFO|tokenization_utils_base.py:2684] 2024-09-05 21:43:19,172 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/checkpoint-511/tokenizer_config.json |
|
[INFO|tokenization_utils_base.py:2693] 2024-09-05 21:43:19,172 >> Special tokens file saved in /content/dissertation/scripts/ner/output/checkpoint-511/special_tokens_map.json |
|
[INFO|tokenization_utils_base.py:2684] 2024-09-05 21:43:21,246 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json |
|
[INFO|tokenization_utils_base.py:2693] 2024-09-05 21:43:21,246 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json |
|
10%|β | 512/5110 [02:22<7:30:20, 5.88s/it]
10%|β | 513/5110 [02:22<5:20:07, 4.18s/it]
10%|β | 514/5110 [02:22<3:49:21, 2.99s/it]
10%|β | 515/5110 [02:22<2:45:57, 2.17s/it]
10%|β | 516/5110 [02:23<2:01:32, 1.59s/it]
10%|β | 517/5110 [02:23<1:29:30, 1.17s/it]
10%|β | 518/5110 [02:23<1:07:04, 1.14it/s]
10%|β | 519/5110 [02:23<53:46, 1.42it/s]
10%|β | 520/5110 [02:24<44:40, 1.71it/s]
10%|β | 521/5110 [02:24<37:35, 2.03it/s]
10%|β | 522/5110 [02:24<32:24, 2.36it/s]
10%|β | 523/5110 [02:24<28:22, 2.69it/s]
10%|β | 524/5110 [02:25<24:52, 3.07it/s]
10%|β | 525/5110 [02:25<22:21, 3.42it/s]
10%|β | 526/5110 [02:25<21:03, 3.63it/s]
10%|β | 527/5110 [02:25<22:05, 3.46it/s]
10%|β | 528/5110 [02:26<23:41, 3.22it/s]
10%|β | 529/5110 [02:26<21:11, 3.60it/s]
10%|β | 530/5110 [02:26<20:51, 3.66it/s]
10%|β | 531/5110 [02:26<19:52, 3.84it/s]
10%|β | 532/5110 [02:27<19:29, 3.92it/s]
10%|β | 533/5110 [02:27<18:53, 4.04it/s]
10%|β | 534/5110 [02:27<18:42, 4.08it/s]
10%|β | 535/5110 [02:27<19:14, 3.96it/s]
10%|β | 536/5110 [02:28<21:52, 3.48it/s]
11%|β | 537/5110 [02:28<21:02, 3.62it/s]
11%|β | 538/5110 [02:28<19:35, 3.89it/s]
11%|β | 539/5110 [02:28<19:09, 3.98it/s]
11%|β | 540/5110 [02:29<19:25, 3.92it/s]
11%|β | 541/5110 [02:29<18:06, 4.21it/s]
11%|β | 542/5110 [02:29<20:07, 3.78it/s]
11%|β | 543/5110 [02:29<20:36, 3.69it/s]
11%|β | 544/5110 [02:30<20:30, 3.71it/s]
11%|β | 545/5110 [02:30<18:47, 4.05it/s]
11%|β | 546/5110 [02:30<18:19, 4.15it/s]
11%|β | 547/5110 [02:30<18:09, 4.19it/s]
11%|β | 548/5110 [02:31<17:22, 4.37it/s]
11%|β | 549/5110 [02:31<17:37, 4.31it/s]
11%|β | 550/5110 [02:31<17:28, 4.35it/s]
11%|β | 551/5110 [02:31<17:23, 4.37it/s]
11%|β | 552/5110 [02:31<16:28, 4.61it/s]
11%|β | 553/5110 [02:32<15:36, 4.87it/s]
11%|β | 554/5110 [02:32<15:33, 4.88it/s]
11%|β | 555/5110 [02:32<16:12, 4.69it/s]
11%|β | 556/5110 [02:32<17:21, 4.37it/s]
11%|β | 557/5110 [02:33<18:09, 4.18it/s]
11%|β | 558/5110 [02:33<18:23, 4.12it/s]
11%|β | 559/5110 [02:33<17:22, 4.36it/s]
11%|β | 560/5110 [02:33<17:00, 4.46it/s]
11%|β | 561/5110 [02:34<17:38, 4.30it/s]
11%|β | 562/5110 [02:34<17:28, 4.34it/s]
11%|β | 563/5110 [02:34<17:48, 4.26it/s]
11%|β | 564/5110 [02:34<19:07, 3.96it/s]
11%|β | 565/5110 [02:35<20:54, 3.62it/s]
11%|β | 566/5110 [02:35<20:59, 3.61it/s]
11%|β | 567/5110 [02:35<19:04, 3.97it/s]
11%|β | 568/5110 [02:35<19:10, 3.95it/s]
11%|β | 569/5110 [02:36<18:02, 4.19it/s]
11%|β | 570/5110 [02:36<20:45, 3.65it/s]
11%|β | 571/5110 [02:36<21:17, 3.55it/s]
11%|β | 572/5110 [02:36<19:56, 3.79it/s]
11%|β | 573/5110 [02:37<19:09, 3.95it/s] |