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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`.
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
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
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
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.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-09-05 21:40:18.144744: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
/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 πŸ€— Transformers. Use `eval_strategy` instead
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
09/05/2024 21:40:20 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
_n_gpu=1,
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},
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=False,
batch_eval_metrics=False,
bf16=False,
bf16_full_eval=False,
data_seed=None,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_persistent_workers=False,
dataloader_pin_memory=True,
dataloader_prefetch_factor=None,
ddp_backend=None,
ddp_broadcast_buffers=None,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
ddp_timeout=1800,
debug=[],
deepspeed=None,
disable_tqdm=False,
dispatch_batches=None,
do_eval=True,
do_predict=True,
do_train=True,
eval_accumulation_steps=None,
eval_delay=0,
eval_do_concat_batches=True,
eval_on_start=False,
eval_steps=None,
eval_strategy=epoch,
eval_use_gather_object=False,
evaluation_strategy=epoch,
fp16=False,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
fsdp=[],
fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False},
fsdp_min_num_params=0,
fsdp_transformer_layer_cls_to_wrap=None,
full_determinism=False,
gradient_accumulation_steps=2,
gradient_checkpointing=False,
gradient_checkpointing_kwargs=None,
greater_is_better=True,
group_by_length=False,
half_precision_backend=auto,
hub_always_push=False,
hub_model_id=None,
hub_private_repo=False,
hub_strategy=every_save,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
include_inputs_for_metrics=False,
include_num_input_tokens_seen=False,
include_tokens_per_second=False,
jit_mode_eval=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=5e-05,
length_column_name=length,
load_best_model_at_end=True,
local_rank=0,
log_level=passive,
log_level_replica=warning,
log_on_each_node=True,
logging_dir=/content/dissertation/scripts/ner/output/tb,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=500,
logging_strategy=steps,
lr_scheduler_kwargs={},
lr_scheduler_type=linear,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=f1,
mp_parameters=,
neftune_noise_alpha=None,
no_cuda=False,
num_train_epochs=10.0,
optim=adamw_torch,
optim_args=None,
optim_target_modules=None,
output_dir=/content/dissertation/scripts/ner/output,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=8,
per_device_train_batch_size=32,
prediction_loss_only=False,
push_to_hub=True,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
ray_scope=last,
remove_unused_columns=True,
report_to=['tensorboard'],
restore_callback_states_from_checkpoint=False,
resume_from_checkpoint=None,
run_name=/content/dissertation/scripts/ner/output,
save_on_each_node=False,
save_only_model=False,
save_safetensors=True,
save_steps=500,
save_strategy=epoch,
save_total_limit=None,
seed=42,
skip_memory_metrics=True,
split_batches=None,
tf32=None,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
torch_empty_cache_steps=None,
torchdynamo=None,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_cpu=False,
use_ipex=False,
use_legacy_prediction_loop=False,
use_mps_device=False,
warmup_ratio=0.0,
warmup_steps=0,
weight_decay=0.0,
)
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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
[INFO|configuration_utils.py:800] 2024-09-05 21:40:33,486 >> 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,
"finetuning_task": "ner",
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"id2label": {
"0": "O",
"1": "B-MORFOLOGIA_NEOPLASIA",
"2": "I-MORFOLOGIA_NEOPLASIA"
},
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"B-MORFOLOGIA_NEOPLASIA": 1,
"I-MORFOLOGIA_NEOPLASIA": 2,
"O": 0
},
"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|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
[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",
"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|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
[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
[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file tokenizer.json from cache at None
[INFO|tokenization_utils_base.py:2269] 2024-09-05 21:40:35,107 >> loading file added_tokens.json from cache at None
[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
[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
[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
[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).
[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']
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 πŸ€— Evaluate: https://huggingface.co/docs/evaluate
metric = load_metric("seqeval", trust_remote_code=True)
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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.
[INFO|trainer.py:2134] 2024-09-05 21:40:59,480 >> ***** Running training *****
[INFO|trainer.py:2135] 2024-09-05 21:40:59,480 >> Num examples = 32,675
[INFO|trainer.py:2136] 2024-09-05 21:40:59,480 >> Num Epochs = 10
[INFO|trainer.py:2137] 2024-09-05 21:40:59,480 >> Instantaneous batch size per device = 32
[INFO|trainer.py:2140] 2024-09-05 21:40:59,480 >> Total train batch size (w. parallel, distributed & accumulation) = 64
[INFO|trainer.py:2141] 2024-09-05 21:40:59,480 >> Gradient Accumulation steps = 2
[INFO|trainer.py:2142] 2024-09-05 21:40:59,480 >> Total optimization steps = 5,110
[INFO|trainer.py:2143] 2024-09-05 21:40:59,481 >> Number of trainable parameters = 124,055,043
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250/5110 [01:02<21:33, 3.76it/s] 5%|▍ | 251/5110 [01:02<20:11, 4.01it/s] 5%|▍ | 252/5110 [01:02<19:47, 4.09it/s] 5%|▍ | 253/5110 [01:02<18:34, 4.36it/s] 5%|▍ | 254/5110 [01:03<17:52, 4.53it/s] 5%|▍ | 255/5110 [01:03<17:25, 4.64it/s] 5%|β–Œ | 256/5110 [01:03<18:18, 4.42it/s] 5%|β–Œ | 257/5110 [01:03<18:36, 4.35it/s] 5%|β–Œ | 258/5110 [01:04<18:14, 4.43it/s] 5%|β–Œ | 259/5110 [01:04<17:51, 4.53it/s] 5%|β–Œ | 260/5110 [01:04<17:48, 4.54it/s] 5%|β–Œ | 261/5110 [01:04<18:08, 4.46it/s] 5%|β–Œ | 262/5110 [01:05<19:23, 4.17it/s] 5%|β–Œ | 263/5110 [01:05<18:11, 4.44it/s] 5%|β–Œ | 264/5110 [01:05<18:35, 4.34it/s] 5%|β–Œ | 265/5110 [01:05<20:47, 3.88it/s] 5%|β–Œ | 266/5110 [01:06<20:20, 3.97it/s] 5%|β–Œ | 267/5110 [01:06<19:45, 4.09it/s] 5%|β–Œ | 268/5110 [01:06<19:14, 4.19it/s] 5%|β–Œ | 269/5110 [01:06<17:44, 4.55it/s] 5%|β–Œ | 270/5110 [01:06<18:16, 4.42it/s] 5%|β–Œ | 271/5110 [01:07<17:57, 4.49it/s] 5%|β–Œ | 272/5110 [01:07<18:26, 4.37it/s] 5%|β–Œ | 273/5110 [01:07<17:19, 4.65it/s] 5%|β–Œ | 274/5110 [01:07<17:32, 4.60it/s] 5%|β–Œ | 275/5110 [01:07<17:27, 4.62it/s] 5%|β–Œ | 276/5110 [01:08<16:29, 4.89it/s] 5%|β–Œ | 277/5110 [01:08<18:20, 4.39it/s] 5%|β–Œ | 278/5110 [01:08<17:23, 4.63it/s] 5%|β–Œ | 279/5110 [01:08<19:30, 4.13it/s] 5%|β–Œ | 280/5110 [01:09<19:06, 4.21it/s] 5%|β–Œ | 281/5110 [01:09<20:17, 3.97it/s] 6%|β–Œ | 282/5110 [01:09<19:39, 4.09it/s] 6%|β–Œ | 283/5110 [01:09<20:23, 3.95it/s] 6%|β–Œ | 284/5110 [01:10<18:57, 4.24it/s] 6%|β–Œ | 285/5110 [01:10<18:55, 4.25it/s] 6%|β–Œ | 286/5110 [01:10<18:58, 4.24it/s] 6%|β–Œ | 287/5110 [01:10<18:44, 4.29it/s] 6%|β–Œ | 288/5110 [01:11<19:08, 4.20it/s] 6%|β–Œ | 289/5110 [01:11<18:27, 4.35it/s] 6%|β–Œ | 290/5110 [01:11<18:38, 4.31it/s] 6%|β–Œ | 291/5110 [01:11<18:57, 4.23it/s] 6%|β–Œ | 292/5110 [01:12<19:24, 4.14it/s] 6%|β–Œ | 293/5110 [01:12<19:26, 4.13it/s] 6%|β–Œ | 294/5110 [01:12<21:31, 3.73it/s] 6%|β–Œ | 295/5110 [01:12<20:44, 3.87it/s] 6%|β–Œ | 296/5110 [01:13<19:15, 4.17it/s] 6%|β–Œ | 297/5110 [01:13<18:16, 4.39it/s] 6%|β–Œ | 298/5110 [01:13<17:46, 4.51it/s] 6%|β–Œ | 299/5110 [01:13<17:36, 4.56it/s] 6%|β–Œ | 300/5110 [01:13<18:00, 4.45it/s] 6%|β–Œ | 301/5110 [01:14<18:01, 4.45it/s] 6%|β–Œ | 302/5110 [01:14<18:53, 4.24it/s] 6%|β–Œ | 303/5110 [01:14<18:06, 4.42it/s] 6%|β–Œ | 304/5110 [01:14<17:02, 4.70it/s] 6%|β–Œ | 305/5110 [01:14<16:42, 4.79it/s] 6%|β–Œ | 306/5110 [01:15<16:42, 4.79it/s] 6%|β–Œ | 307/5110 [01:15<15:50, 5.05it/s] 6%|β–Œ | 308/5110 [01:15<15:37, 5.12it/s] 6%|β–Œ | 309/5110 [01:15<16:48, 4.76it/s] 6%|β–Œ | 310/5110 [01:15<17:15, 4.64it/s] 6%|β–Œ | 311/5110 [01:16<16:50, 4.75it/s] 6%|β–Œ | 312/5110 [01:16<16:51, 4.74it/s] 6%|β–Œ | 313/5110 [01:16<18:00, 4.44it/s] 6%|β–Œ | 314/5110 [01:16<17:19, 4.61it/s] 6%|β–Œ | 315/5110 [01:17<16:56, 4.72it/s] 6%|β–Œ | 316/5110 [01:17<16:53, 4.73it/s] 6%|β–Œ | 317/5110 [01:17<17:01, 4.69it/s] 6%|β–Œ | 318/5110 [01:17<16:36, 4.81it/s] 6%|β–Œ | 319/5110 [01:17<17:25, 4.58it/s] 6%|β–‹ | 320/5110 [01:18<17:41, 4.51it/s] 6%|β–‹ | 321/5110 [01:18<17:29, 4.56it/s] 6%|β–‹ | 322/5110 [01:18<17:26, 4.58it/s] 6%|β–‹ | 323/5110 [01:18<17:22, 4.59it/s] 6%|β–‹ | 324/5110 [01:19<18:04, 4.42it/s] 6%|β–‹ | 325/5110 [01:19<18:21, 4.34it/s] 6%|β–‹ | 326/5110 [01:19<18:41, 4.27it/s] 6%|β–‹ | 327/5110 [01:19<19:30, 4.09it/s] 6%|β–‹ | 328/5110 [01:19<18:14, 4.37it/s] 6%|β–‹ | 329/5110 [01:20<17:25, 4.57it/s] 6%|β–‹ | 330/5110 [01:20<16:54, 4.71it/s] 6%|β–‹ | 331/5110 [01:20<18:19, 4.35it/s] 6%|β–‹ | 332/5110 [01:20<18:10, 4.38it/s] 7%|β–‹ | 333/5110 [01:21<17:23, 4.58it/s] 7%|β–‹ | 334/5110 [01:21<21:38, 3.68it/s] 7%|β–‹ | 335/5110 [01:21<20:50, 3.82it/s] 7%|β–‹ | 336/5110 [01:21<21:36, 3.68it/s] 7%|β–‹ | 337/5110 [01:22<20:28, 3.89it/s] 7%|β–‹ | 338/5110 [01:22<19:46, 4.02it/s] 7%|β–‹ | 339/5110 [01:22<19:29, 4.08it/s] 7%|β–‹ | 340/5110 [01:22<18:18, 4.34it/s] 7%|β–‹ | 341/5110 [01:23<18:27, 4.31it/s] 7%|β–‹ | 342/5110 [01:23<17:18, 4.59it/s] 7%|β–‹ | 343/5110 [01:23<17:55, 4.43it/s] 7%|β–‹ | 344/5110 [01:23<19:35, 4.05it/s] 7%|β–‹ | 345/5110 [01:24<18:48, 4.22it/s] 7%|β–‹ | 346/5110 [01:24<19:01, 4.17it/s] 7%|β–‹ | 347/5110 [01:24<19:01, 4.17it/s] 7%|β–‹ | 348/5110 [01:24<19:28, 4.08it/s] 7%|β–‹ | 349/5110 [01:25<20:43, 3.83it/s] 7%|β–‹ | 350/5110 [01:25<19:11, 4.13it/s] 7%|β–‹ | 351/5110 [01:25<18:25, 4.30it/s] 7%|β–‹ | 352/5110 [01:25<19:25, 4.08it/s] 7%|β–‹ | 353/5110 [01:26<19:23, 4.09it/s] 7%|β–‹ | 354/5110 [01:26<20:57, 3.78it/s] 7%|β–‹ | 355/5110 [01:26<19:32, 4.06it/s] 7%|β–‹ | 356/5110 [01:26<19:10, 4.13it/s] 7%|β–‹ | 357/5110 [01:27<19:14, 4.12it/s] 7%|β–‹ | 358/5110 [01:27<18:54, 4.19it/s] 7%|β–‹ | 359/5110 [01:27<18:48, 4.21it/s] 7%|β–‹ | 360/5110 [01:27<18:41, 4.24it/s] 7%|β–‹ | 361/5110 [01:28<20:02, 3.95it/s] 7%|β–‹ | 362/5110 [01:28<21:10, 3.74it/s] 7%|β–‹ | 363/5110 [01:28<20:45, 3.81it/s] 7%|β–‹ | 364/5110 [01:28<20:42, 3.82it/s] 7%|β–‹ | 365/5110 [01:29<19:26, 4.07it/s] 7%|β–‹ | 366/5110 [01:29<20:55, 3.78it/s] 7%|β–‹ | 367/5110 [01:29<19:41, 4.01it/s] 7%|β–‹ | 368/5110 [01:29<20:05, 3.93it/s] 7%|β–‹ | 369/5110 [01:30<19:21, 4.08it/s] 7%|β–‹ | 370/5110 [01:30<19:10, 4.12it/s] 7%|β–‹ | 371/5110 [01:30<18:21, 4.30it/s] 7%|β–‹ | 372/5110 [01:30<17:59, 4.39it/s] 7%|β–‹ | 373/5110 [01:31<20:23, 3.87it/s] 7%|β–‹ | 374/5110 [01:31<19:08, 4.12it/s] 7%|β–‹ | 375/5110 [01:31<19:38, 4.02it/s] 7%|β–‹ | 376/5110 [01:31<20:23, 3.87it/s] 7%|β–‹ | 377/5110 [01:32<20:24, 3.87it/s] 7%|β–‹ | 378/5110 [01:32<21:52, 3.60it/s] 7%|β–‹ | 379/5110 [01:32<19:53, 3.96it/s] 7%|β–‹ | 380/5110 [01:32<18:59, 4.15it/s] 7%|β–‹ | 381/5110 [01:32<17:32, 4.49it/s] 7%|β–‹ | 382/5110 [01:33<18:13, 4.32it/s] 7%|β–‹ | 383/5110 [01:33<20:03, 3.93it/s] 8%|β–Š | 384/5110 [01:33<18:50, 4.18it/s] 8%|β–Š | 385/5110 [01:33<18:33, 4.24it/s] 8%|β–Š | 386/5110 [01:34<18:51, 4.18it/s] 8%|β–Š | 387/5110 [01:34<18:45, 4.20it/s] 8%|β–Š | 388/5110 [01:34<19:19, 4.07it/s] 8%|β–Š | 389/5110 [01:34<18:15, 4.31it/s] 8%|β–Š | 390/5110 [01:35<17:07, 4.59it/s] 8%|β–Š | 391/5110 [01:35<16:22, 4.80it/s] 8%|β–Š | 392/5110 [01:35<17:21, 4.53it/s] 8%|β–Š | 393/5110 [01:35<18:45, 4.19it/s] 8%|β–Š | 394/5110 [01:35<17:50, 4.41it/s] 8%|β–Š | 395/5110 [01:36<16:20, 4.81it/s] 8%|β–Š | 396/5110 [01:36<17:09, 4.58it/s] 8%|β–Š | 397/5110 [01:36<16:42, 4.70it/s] 8%|β–Š | 398/5110 [01:36<19:24, 4.05it/s] 8%|β–Š | 399/5110 [01:37<18:06, 4.34it/s] 8%|β–Š | 400/5110 [01:37<17:10, 4.57it/s] 8%|β–Š | 401/5110 [01:37<16:11, 4.85it/s] 8%|β–Š | 402/5110 [01:37<15:31, 5.05it/s] 8%|β–Š | 403/5110 [01:37<16:22, 4.79it/s] 8%|β–Š | 404/5110 [01:38<18:42, 4.19it/s] 8%|β–Š | 405/5110 [01:38<18:00, 4.35it/s] 8%|β–Š | 406/5110 [01:38<18:01, 4.35it/s] 8%|β–Š | 407/5110 [01:38<18:11, 4.31it/s] 8%|β–Š | 408/5110 [01:39<17:29, 4.48it/s] 8%|β–Š | 409/5110 [01:39<19:44, 3.97it/s] 8%|β–Š | 410/5110 [01:39<18:19, 4.27it/s] 8%|β–Š | 411/5110 [01:39<20:42, 3.78it/s] 8%|β–Š | 412/5110 [01:40<18:37, 4.20it/s] 8%|β–Š | 413/5110 [01:40<17:57, 4.36it/s] 8%|β–Š | 414/5110 [01:40<18:08, 4.31it/s] 8%|β–Š | 415/5110 [01:40<18:35, 4.21it/s] 8%|β–Š | 416/5110 [01:41<18:17, 4.28it/s] 8%|β–Š | 417/5110 [01:41<18:06, 4.32it/s] 8%|β–Š | 418/5110 [01:41<17:28, 4.47it/s] 8%|β–Š | 419/5110 [01:41<19:48, 3.95it/s] 8%|β–Š | 420/5110 [01:41<19:07, 4.09it/s] 8%|β–Š | 421/5110 [01:42<20:14, 3.86it/s] 8%|β–Š | 422/5110 [01:42<19:21, 4.04it/s] 8%|β–Š | 423/5110 [01:42<18:30, 4.22it/s] 8%|β–Š | 424/5110 [01:42<18:36, 4.20it/s] 8%|β–Š | 425/5110 [01:43<17:52, 4.37it/s] 8%|β–Š | 426/5110 [01:43<18:07, 4.31it/s] 8%|β–Š | 427/5110 [01:43<19:34, 3.99it/s] 8%|β–Š | 428/5110 [01:43<19:33, 3.99it/s] 8%|β–Š | 429/5110 [01:44<19:26, 4.01it/s] 8%|β–Š | 430/5110 [01:44<19:03, 4.09it/s] 8%|β–Š | 431/5110 [01:44<20:21, 3.83it/s] 8%|β–Š | 432/5110 [01:44<19:23, 4.02it/s] 8%|β–Š | 433/5110 [01:45<17:33, 4.44it/s] 8%|β–Š | 434/5110 [01:45<17:16, 4.51it/s] 9%|β–Š | 435/5110 [01:45<18:13, 4.28it/s] 9%|β–Š | 436/5110 [01:45<17:17, 4.50it/s] 9%|β–Š | 437/5110 [01:46<20:06, 3.87it/s] 9%|β–Š | 438/5110 [01:46<18:47, 4.14it/s] 9%|β–Š | 439/5110 [01:46<18:15, 4.26it/s] 9%|β–Š | 440/5110 [01:46<17:16, 4.50it/s] 9%|β–Š | 441/5110 [01:46<17:11, 4.53it/s] 9%|β–Š | 442/5110 [01:47<17:03, 4.56it/s] 9%|β–Š | 443/5110 [01:47<16:58, 4.58it/s] 9%|β–Š | 444/5110 [01:47<18:27, 4.21it/s] 9%|β–Š | 445/5110 [01:47<18:27, 4.21it/s] 9%|β–Š | 446/5110 [01:48<18:10, 4.28it/s] 9%|β–Š | 447/5110 [01:48<19:21, 4.02it/s] 9%|β–‰ | 448/5110 [01:48<17:55, 4.33it/s] 9%|β–‰ | 449/5110 [01:48<17:54, 4.34it/s] 9%|β–‰ | 450/5110 [01:49<18:09, 4.28it/s] 9%|β–‰ | 451/5110 [01:49<17:21, 4.47it/s] 9%|β–‰ | 452/5110 [01:49<17:32, 4.43it/s] 9%|β–‰ | 453/5110 [01:49<18:36, 4.17it/s] 9%|β–‰ | 454/5110 [01:50<17:53, 4.34it/s] 9%|β–‰ | 455/5110 [01:50<17:36, 4.41it/s] 9%|β–‰ | 456/5110 [01:50<16:56, 4.58it/s] 9%|β–‰ | 457/5110 [01:50<16:07, 4.81it/s] 9%|β–‰ | 458/5110 [01:50<18:38, 4.16it/s] 9%|β–‰ | 459/5110 [01:51<17:21, 4.47it/s] 9%|β–‰ | 460/5110 [01:51<17:29, 4.43it/s] 9%|β–‰ | 461/5110 [01:51<16:23, 4.73it/s] 9%|β–‰ | 462/5110 [01:51<16:37, 4.66it/s] 9%|β–‰ | 463/5110 [01:51<16:45, 4.62it/s] 9%|β–‰ | 464/5110 [01:52<17:03, 4.54it/s] 9%|β–‰ | 465/5110 [01:52<17:45, 4.36it/s] 9%|β–‰ | 466/5110 [01:52<17:18, 4.47it/s] 9%|β–‰ | 467/5110 [01:52<18:32, 4.17it/s] 9%|β–‰ | 468/5110 [01:53<17:48, 4.34it/s] 9%|β–‰ | 469/5110 [01:53<17:39, 4.38it/s] 9%|β–‰ | 470/5110 [01:53<17:40, 4.38it/s] 9%|β–‰ | 471/5110 [01:53<16:34, 4.67it/s] 9%|β–‰ | 472/5110 [01:53<16:19, 4.74it/s] 9%|β–‰ | 473/5110 [01:54<16:53, 4.58it/s] 9%|β–‰ | 474/5110 [01:54<17:21, 4.45it/s] 9%|β–‰ | 475/5110 [01:54<16:21, 4.72it/s] 9%|β–‰ | 476/5110 [01:54<17:58, 4.30it/s] 9%|β–‰ | 477/5110 [01:55<17:04, 4.52it/s] 9%|β–‰ | 478/5110 [01:55<16:11, 4.77it/s] 9%|β–‰ | 479/5110 [01:55<17:09, 4.50it/s] 9%|β–‰ | 480/5110 [01:55<17:22, 4.44it/s] 9%|β–‰ | 481/5110 [01:56<17:44, 4.35it/s] 9%|β–‰ | 482/5110 [01:56<18:01, 4.28it/s] 9%|β–‰ | 483/5110 [01:56<17:27, 4.42it/s] 9%|β–‰ | 484/5110 [01:56<17:44, 4.35it/s] 9%|β–‰ | 485/5110 [01:56<18:01, 4.27it/s] 10%|β–‰ | 486/5110 [01:57<17:27, 4.41it/s] 10%|β–‰ | 487/5110 [01:57<17:25, 4.42it/s] 10%|β–‰ | 488/5110 [01:57<16:54, 4.56it/s] 10%|β–‰ | 489/5110 [01:57<19:23, 3.97it/s] 10%|β–‰ | 490/5110 [01:58<17:53, 4.30it/s] 10%|β–‰ | 491/5110 [01:58<17:57, 4.29it/s] 10%|β–‰ | 492/5110 [01:58<17:20, 4.44it/s] 10%|β–‰ | 493/5110 [01:58<18:21, 4.19it/s] 10%|β–‰ | 494/5110 [01:59<17:23, 4.42it/s] 10%|β–‰ | 495/5110 [01:59<18:03, 4.26it/s] 10%|β–‰ | 496/5110 [01:59<17:43, 4.34it/s] 10%|β–‰ | 497/5110 [01:59<18:21, 4.19it/s] 10%|β–‰ | 498/5110 [01:59<18:25, 4.17it/s] 10%|β–‰ | 499/5110 [02:00<19:14, 3.99it/s] 10%|β–‰ | 500/5110 [02:00<18:12, 4.22it/s] 10%|β–‰ | 500/5110 [02:00<18:12, 4.22it/s] 10%|β–‰ | 501/5110 [02:00<19:24, 3.96it/s] 10%|β–‰ | 502/5110 [02:01<19:28, 3.94it/s] 10%|β–‰ | 503/5110 [02:01<18:31, 4.14it/s] 10%|β–‰ | 504/5110 [02:01<17:48, 4.31it/s] 10%|β–‰ | 505/5110 [02:01<17:23, 4.41it/s] 10%|β–‰ | 506/5110 [02:01<18:47, 4.08it/s] 10%|β–‰ | 507/5110 [02:02<18:44, 4.09it/s] 10%|β–‰ | 508/5110 [02:02<17:37, 4.35it/s] 10%|β–‰ | 509/5110 [02:02<18:05, 4.24it/s] 10%|β–‰ | 510/5110 [02:02<17:30, 4.38it/s] 10%|β–ˆ | 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 >>
***** Running Evaluation *****
[INFO|trainer.py:3821] 2024-09-05 21:43:02,477 >> Num examples = 7354
[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}
0%| | 0/920 [00:00<?, ?it/s]
1%| | 9/920 [00:00<00:10, 89.53it/s]
2%|▏ | 18/920 [00:00<00:11, 80.67it/s]
3%|β–Ž | 27/920 [00:00<00:11, 80.20it/s]
4%|▍ | 36/920 [00:00<00:11, 80.15it/s]
5%|▍ | 45/920 [00:00<00:10, 80.03it/s]
6%|β–Œ | 54/920 [00:00<00:11, 75.91it/s]
7%|β–‹ | 62/920 [00:00<00:11, 73.99it/s]
8%|β–Š | 70/920 [00:00<00:11, 74.77it/s]
9%|β–Š | 79/920 [00:01<00:10, 77.39it/s]
9%|β–‰ | 87/920 [00:01<00:10, 77.95it/s]
10%|β–ˆ | 95/920 [00:01<00:10, 77.87it/s]
11%|β–ˆ | 103/920 [00:01<00:10, 78.49it/s]
12%|β–ˆβ– | 111/920 [00:01<00:10, 78.11it/s]
13%|β–ˆβ–Ž | 120/920 [00:01<00:10, 78.92it/s]
14%|β–ˆβ– | 128/920 [00:01<00:10, 74.71it/s]
15%|β–ˆβ– | 137/920 [00:01<00:10, 77.16it/s]
16%|β–ˆβ–Œ | 146/920 [00:01<00:09, 79.00it/s]
17%|β–ˆβ–‹ | 154/920 [00:01<00:09, 79.03it/s]
18%|β–ˆβ–Š | 163/920 [00:02<00:09, 79.61it/s]
19%|β–ˆβ–Š | 172/920 [00:02<00:09, 81.23it/s]
20%|β–ˆβ–‰ | 181/920 [00:02<00:09, 81.86it/s]
21%|β–ˆβ–ˆ | 190/920 [00:02<00:08, 82.13it/s]
22%|β–ˆβ–ˆβ– | 199/920 [00:02<00:08, 81.55it/s]
23%|β–ˆβ–ˆβ–Ž | 208/920 [00:02<00:09, 77.57it/s]
24%|β–ˆβ–ˆβ–Ž | 217/920 [00:02<00:08, 78.97it/s]
24%|β–ˆβ–ˆβ– | 225/920 [00:02<00:08, 79.25it/s]
25%|β–ˆβ–ˆβ–Œ | 234/920 [00:02<00:08, 81.15it/s]
26%|β–ˆβ–ˆβ–‹ | 243/920 [00:03<00:08, 82.39it/s]
27%|β–ˆβ–ˆβ–‹ | 252/920 [00:03<00:08, 80.82it/s]
28%|β–ˆβ–ˆβ–Š | 261/920 [00:03<00:08, 79.20it/s]
29%|β–ˆβ–ˆβ–‰ | 269/920 [00:03<00:08, 79.24it/s]
30%|β–ˆβ–ˆβ–ˆ | 278/920 [00:03<00:07, 80.57it/s]
31%|β–ˆβ–ˆβ–ˆ | 287/920 [00:03<00:07, 80.61it/s]
32%|β–ˆβ–ˆβ–ˆβ– | 296/920 [00:03<00:07, 80.74it/s]
33%|β–ˆβ–ˆβ–ˆβ–Ž | 305/920 [00:03<00:07, 80.19it/s]
34%|β–ˆβ–ˆβ–ˆβ– | 314/920 [00:03<00:07, 80.93it/s]
35%|β–ˆβ–ˆβ–ˆβ–Œ | 323/920 [00:04<00:07, 79.78it/s]
36%|β–ˆβ–ˆβ–ˆβ–Œ | 331/920 [00:04<00:07, 79.02it/s]
37%|β–ˆβ–ˆβ–ˆβ–‹ | 339/920 [00:04<00:07, 76.52it/s]
38%|β–ˆβ–ˆβ–ˆβ–Š | 347/920 [00:04<00:07, 76.64it/s]
39%|β–ˆβ–ˆβ–ˆβ–Š | 355/920 [00:04<00:07, 77.24it/s]
39%|β–ˆβ–ˆβ–ˆβ–‰ | 363/920 [00:04<00:07, 77.76it/s]
40%|β–ˆβ–ˆβ–ˆβ–ˆ | 372/920 [00:04<00:06, 78.98it/s]
41%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 381/920 [00:04<00:06, 80.50it/s]
42%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 390/920 [00:04<00:06, 80.32it/s]
43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 399/920 [00:05<00:06, 76.14it/s]
44%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 407/920 [00:05<00:06, 74.87it/s]
45%|β–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 416/920 [00:05<00:06, 76.95it/s]
46%|β–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 425/920 [00:05<00:06, 78.23it/s]
47%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 434/920 [00:05<00:06, 79.25it/s]
48%|β–ˆβ–ˆβ–ˆβ–ˆβ–Š | 443/920 [00:05<00:05, 80.48it/s]
49%|β–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 452/920 [00:05<00:05, 80.80it/s]
50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 461/920 [00:05<00:05, 80.93it/s]
51%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 470/920 [00:05<00:05, 80.02it/s]
52%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 479/920 [00:06<00:05, 80.23it/s]
53%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 488/920 [00:06<00:05, 80.26it/s]
54%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 497/920 [00:06<00:05, 80.36it/s]
55%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 506/920 [00:06<00:05, 81.30it/s]
56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 515/920 [00:06<00:04, 81.42it/s]
57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 524/920 [00:06<00:04, 81.62it/s]
58%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 533/920 [00:06<00:04, 81.99it/s]
59%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 542/920 [00:06<00:04, 81.88it/s]
60%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 551/920 [00:06<00:04, 78.04it/s]
61%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 559/920 [00:07<00:04, 76.38it/s]
62%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 568/920 [00:07<00:04, 77.68it/s]
63%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 577/920 [00:07<00:04, 79.04it/s]
64%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 585/920 [00:07<00:04, 78.90it/s]
65%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 594/920 [00:07<00:04, 80.30it/s]
66%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 603/920 [00:07<00:03, 81.40it/s]
67%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 612/920 [00:07<00:03, 81.11it/s]
68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 621/920 [00:07<00:03, 79.75it/s]
68%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 629/920 [00:07<00:03, 77.84it/s]
69%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 637/920 [00:08<00:03, 77.80it/s]
70%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 646/920 [00:08<00:03, 78.99it/s]
71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 655/920 [00:08<00:03, 79.72it/s]
72%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 664/920 [00:08<00:03, 80.67it/s]
73%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 673/920 [00:08<00:03, 81.27it/s]
74%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 682/920 [00:08<00:02, 82.04it/s]
75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 691/920 [00:08<00:02, 81.85it/s]
76%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 700/920 [00:08<00:02, 81.24it/s]
77%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 709/920 [00:08<00:02, 80.14it/s]
78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 718/920 [00:09<00:02, 80.64it/s]
79%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 727/920 [00:09<00:02, 81.54it/s]
80%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 736/920 [00:09<00:02, 81.40it/s]
81%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 745/920 [00:09<00:02, 77.96it/s]
82%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 754/920 [00:09<00:02, 79.48it/s]
83%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 762/920 [00:09<00:02, 78.68it/s]
84%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 771/920 [00:09<00:01, 80.44it/s]
85%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 780/920 [00:09<00:01, 79.54it/s]
86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 789/920 [00:09<00:01, 80.86it/s]
87%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 798/920 [00:10<00:01, 80.98it/s]
88%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 807/920 [00:10<00:01, 78.75it/s]
89%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 816/920 [00:10<00:01, 79.89it/s]
90%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 825/920 [00:10<00:01, 81.14it/s]
91%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 834/920 [00:10<00:01, 81.82it/s]
92%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–| 843/920 [00:10<00:00, 82.50it/s]
93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 852/920 [00:10<00:00, 79.23it/s]
93%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž| 860/920 [00:10<00:00, 77.71it/s]
94%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–| 868/920 [00:10<00:00, 68.84it/s]
95%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ| 877/920 [00:11<00:00, 73.34it/s]
96%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 886/920 [00:11<00:00, 75.71it/s]
97%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 894/920 [00:11<00:00, 73.74it/s]
98%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š| 902/920 [00:11<00:00, 74.81it/s]
99%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰| 910/920 [00:11<00:00, 74.55it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰| 918/920 [00:11<00:00, 75.64it/s]
 10%|β–ˆ | 511/5110 [02:18<15:48, 4.85it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 920/920 [00:15<00:00, 75.64it/s]
[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–ˆ | 512/5110 [02:22<7:30:20, 5.88s/it] 10%|β–ˆ | 513/5110 [02:22<5:20:07, 4.18s/it] 10%|β–ˆ | 514/5110 [02:22<3:49:21, 2.99s/it] 10%|β–ˆ | 515/5110 [02:22<2:45:57, 2.17s/it] 10%|β–ˆ | 516/5110 [02:23<2:01:32, 1.59s/it] 10%|β–ˆ | 517/5110 [02:23<1:29:30, 1.17s/it] 10%|β–ˆ | 518/5110 [02:23<1:07:04, 1.14it/s] 10%|β–ˆ | 519/5110 [02:23<53:46, 1.42it/s] 10%|β–ˆ | 520/5110 [02:24<44:40, 1.71it/s] 10%|β–ˆ | 521/5110 [02:24<37:35, 2.03it/s] 10%|β–ˆ | 522/5110 [02:24<32:24, 2.36it/s] 10%|β–ˆ | 523/5110 [02:24<28:22, 2.69it/s] 10%|β–ˆ | 524/5110 [02:25<24:52, 3.07it/s] 10%|β–ˆ | 525/5110 [02:25<22:21, 3.42it/s] 10%|β–ˆ | 526/5110 [02:25<21:03, 3.63it/s] 10%|β–ˆ | 527/5110 [02:25<22:05, 3.46it/s] 10%|β–ˆ | 528/5110 [02:26<23:41, 3.22it/s] 10%|β–ˆ | 529/5110 [02:26<21:11, 3.60it/s] 10%|β–ˆ | 530/5110 [02:26<20:51, 3.66it/s] 10%|β–ˆ | 531/5110 [02:26<19:52, 3.84it/s] 10%|β–ˆ | 532/5110 [02:27<19:29, 3.92it/s] 10%|β–ˆ | 533/5110 [02:27<18:53, 4.04it/s] 10%|β–ˆ | 534/5110 [02:27<18:42, 4.08it/s] 10%|β–ˆ | 535/5110 [02:27<19:14, 3.96it/s] 10%|β–ˆ | 536/5110 [02:28<21:52, 3.48it/s] 11%|β–ˆ | 537/5110 [02:28<21:02, 3.62it/s] 11%|β–ˆ | 538/5110 [02:28<19:35, 3.89it/s] 11%|β–ˆ | 539/5110 [02:28<19:09, 3.98it/s] 11%|β–ˆ | 540/5110 [02:29<19:25, 3.92it/s] 11%|β–ˆ | 541/5110 [02:29<18:06, 4.21it/s] 11%|β–ˆ | 542/5110 [02:29<20:07, 3.78it/s] 11%|β–ˆ | 543/5110 [02:29<20:36, 3.69it/s] 11%|β–ˆ | 544/5110 [02:30<20:30, 3.71it/s] 11%|β–ˆ | 545/5110 [02:30<18:47, 4.05it/s] 11%|β–ˆ | 546/5110 [02:30<18:19, 4.15it/s] 11%|β–ˆ | 547/5110 [02:30<18:09, 4.19it/s] 11%|β–ˆ | 548/5110 [02:31<17:22, 4.37it/s] 11%|β–ˆ | 549/5110 [02:31<17:37, 4.31it/s] 11%|β–ˆ | 550/5110 [02:31<17:28, 4.35it/s] 11%|β–ˆ | 551/5110 [02:31<17:23, 4.37it/s] 11%|β–ˆ | 552/5110 [02:31<16:28, 4.61it/s] 11%|β–ˆ | 553/5110 [02:32<15:36, 4.87it/s] 11%|β–ˆ | 554/5110 [02:32<15:33, 4.88it/s] 11%|β–ˆ | 555/5110 [02:32<16:12, 4.69it/s] 11%|β–ˆ | 556/5110 [02:32<17:21, 4.37it/s] 11%|β–ˆ | 557/5110 [02:33<18:09, 4.18it/s] 11%|β–ˆ | 558/5110 [02:33<18:23, 4.12it/s] 11%|β–ˆ | 559/5110 [02:33<17:22, 4.36it/s] 11%|β–ˆ | 560/5110 [02:33<17:00, 4.46it/s] 11%|β–ˆ | 561/5110 [02:34<17:38, 4.30it/s] 11%|β–ˆ | 562/5110 [02:34<17:28, 4.34it/s] 11%|β–ˆ | 563/5110 [02:34<17:48, 4.26it/s] 11%|β–ˆ | 564/5110 [02:34<19:07, 3.96it/s] 11%|β–ˆ | 565/5110 [02:35<20:54, 3.62it/s] 11%|β–ˆ | 566/5110 [02:35<20:59, 3.61it/s] 11%|β–ˆ | 567/5110 [02:35<19:04, 3.97it/s] 11%|β–ˆ | 568/5110 [02:35<19:10, 3.95it/s] 11%|β–ˆ | 569/5110 [02:36<18:02, 4.19it/s] 11%|β–ˆ | 570/5110 [02:36<20:45, 3.65it/s] 11%|β–ˆ | 571/5110 [02:36<21:17, 3.55it/s] 11%|β–ˆ | 572/5110 [02:36<19:56, 3.79it/s] 11%|β–ˆ | 573/5110 [02:37<19:09, 3.95it/s]