| 06/19/2024 22:00:21 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False | |
| 06/19/2024 22:00:21 - INFO - __main__ - Training/evaluation parameters TrainingArguments( | |
| _n_gpu=1, | |
| adafactor=False, | |
| adam_beta1=0.9, | |
| adam_beta2=0.999, | |
| adam_epsilon=1e-08, | |
| auto_find_batch_size=False, | |
| bf16=False, | |
| bf16_full_eval=False, | |
| data_seed=None, | |
| dataloader_drop_last=False, | |
| dataloader_num_workers=0, | |
| dataloader_pin_memory=True, | |
| ddp_bucket_cap_mb=None, | |
| ddp_find_unused_parameters=None, | |
| ddp_timeout=1800, | |
| debug=[], | |
| deepspeed=None, | |
| disable_tqdm=False, | |
| do_eval=False, | |
| do_predict=True, | |
| do_train=False, | |
| eval_accumulation_steps=None, | |
| eval_delay=0, | |
| eval_steps=None, | |
| evaluation_strategy=no, | |
| fp16=False, | |
| fp16_backend=auto, | |
| fp16_full_eval=False, | |
| fp16_opt_level=O1, | |
| fsdp=[], | |
| fsdp_min_num_params=0, | |
| fsdp_transformer_layer_cls_to_wrap=None, | |
| full_determinism=False, | |
| gradient_accumulation_steps=1, | |
| gradient_checkpointing=False, | |
| greater_is_better=None, | |
| group_by_length=False, | |
| half_precision_backend=auto, | |
| 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, | |
| 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=False, | |
| local_rank=-1, | |
| log_level=passive, | |
| log_level_replica=passive, | |
| log_on_each_node=True, | |
| logging_dir=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/runs/Jun19_22-00-21_ppi-nlp6, | |
| logging_first_step=False, | |
| logging_nan_inf_filter=True, | |
| logging_steps=500, | |
| logging_strategy=steps, | |
| lr_scheduler_type=linear, | |
| max_grad_norm=1.0, | |
| max_steps=-1, | |
| metric_for_best_model=None, | |
| mp_parameters=, | |
| no_cuda=False, | |
| num_train_epochs=3.0, | |
| optim=adamw_hf, | |
| optim_args=None, | |
| output_dir=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41, | |
| overwrite_output_dir=False, | |
| past_index=-1, | |
| per_device_eval_batch_size=4, | |
| per_device_train_batch_size=8, | |
| prediction_loss_only=False, | |
| push_to_hub=False, | |
| 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=[], | |
| resume_from_checkpoint=None, | |
| run_name=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41, | |
| save_on_each_node=False, | |
| save_steps=500, | |
| save_strategy=steps, | |
| save_total_limit=None, | |
| seed=42, | |
| sharded_ddp=[], | |
| skip_memory_metrics=True, | |
| tf32=None, | |
| torch_compile=False, | |
| torch_compile_backend=None, | |
| torch_compile_mode=None, | |
| torchdynamo=None, | |
| tpu_metrics_debug=False, | |
| tpu_num_cores=None, | |
| use_ipex=False, | |
| use_legacy_prediction_loop=False, | |
| use_mps_device=False, | |
| warmup_ratio=0.0, | |
| warmup_steps=0, | |
| weight_decay=0.0, | |
| xpu_backend=None, | |
| ) | |
| /home/ext_maiara_frodrigues2000_gmail_/.pyenv/versions/spokennlp/lib/python3.8/site-packages/datasets/load.py:2555: FutureWarning: 'ignore_verifications' was deprecated in favor of 'verification_mode' in version 2.9.1 and will be removed in 3.0.0. | |
| You can remove this warning by passing 'verification_mode=no_checks' instead. | |
| warnings.warn( | |
| /home/ext_maiara_frodrigues2000_gmail_/.pyenv/versions/spokennlp/lib/python3.8/site-packages/datasets/load.py:929: FutureWarning: The repository for wiki_section_city contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at ./src/datasets/wiki_section_city/wiki_section_city.py | |
| You can avoid this message in future by passing the argument `trust_remote_code=True`. | |
| Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`. | |
| warnings.warn( | |
| No config specified, defaulting to the single config: wiki_section_city/WikiSectionCityForDocumentSegmentation | |
| 06/19/2024 22:00:21 - INFO - datasets.builder - No config specified, defaulting to the single config: wiki_section_city/WikiSectionCityForDocumentSegmentation | |
| Using custom data configuration WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad | |
| 06/19/2024 22:00:21 - INFO - datasets.builder - Using custom data configuration WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad | |
| Loading Dataset Infos from /home/ext_luti4497_gmail_com/.cache/huggingface/modules/datasets_modules/datasets/wiki_section_city/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4 | |
| 06/19/2024 22:00:21 - INFO - datasets.info - Loading Dataset Infos from /home/ext_luti4497_gmail_com/.cache/huggingface/modules/datasets_modules/datasets/wiki_section_city/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4 | |
| Generating dataset wiki_section_city (/projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4) | |
| 06/19/2024 22:00:21 - INFO - datasets.builder - Generating dataset wiki_section_city (/projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4) | |
| Downloading and preparing dataset wiki_section_city/WikiSectionCityForDocumentSegmentation to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4... | |
| 06/19/2024 22:00:21 - INFO - datasets.builder - Downloading and preparing dataset wiki_section_city/WikiSectionCityForDocumentSegmentation to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4... | |
| Downloading took 0.0 min | |
| 06/19/2024 22:00:21 - INFO - datasets.download.download_manager - Downloading took 0.0 min | |
| Checksum Computation took 0.0 min | |
| 06/19/2024 22:00:21 - INFO - datasets.download.download_manager - Checksum Computation took 0.0 min | |
| Generating train split | |
| 06/19/2024 22:00:21 - INFO - datasets.builder - Generating train split | |
| Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 1 examples [00:00, 1.88 examples/s] Generating train split: 174 examples [00:00, 366.96 examples/s] Generating train split: 332 examples [00:00, 647.83 examples/s] Generating train split: 497 examples [00:00, 889.10 examples/s] Generating train split: 684 examples [00:00, 1141.68 examples/s] Generating train split: 873 examples [00:01, 1341.00 examples/s] Generating train split: 1086 examples [00:01, 1212.55 examples/s] Generating train split: 1257 examples [00:01, 1324.98 examples/s] Generating train split: 1459 examples [00:01, 1496.72 examples/s] Generating train split: 1642 examples [00:01, 1581.27 examples/s] Generating train split: 1815 examples [00:01, 1615.68 examples/s] Generating train split: 2000 examples [00:01, 1338.66 examples/s] Generating train split: 2170 examples [00:01, 1423.52 examples/s] Generating train split: 2420 examples [00:02, 1504.76 examples/s] Generating train split: 2632 examples [00:02, 1471.35 examples/s] Generating train split: 2843 examples [00:02, 1619.36 examples/s] Generating train split: 3074 examples [00:02, 1345.54 examples/s] Generating train split: 3246 examples [00:02, 1419.60 examples/s] Generating train split: 3444 examples [00:02, 1548.34 examples/s] Generating train split: 3631 examples [00:02, 1622.73 examples/s] Generating train split: 3807 examples [00:02, 1647.77 examples/s] Generating train split: 4000 examples [00:03, 1339.79 examples/s] Generating train split: 4221 examples [00:03, 1378.81 examples/s] Generating train split: 4394 examples [00:03, 1450.17 examples/s] Generating train split: 4581 examples [00:03, 1551.81 examples/s] Generating train split: 4746 examples [00:03, 1577.15 examples/s] Generating train split: 4915 examples [00:03, 1601.50 examples/s] Generating train split: 5083 examples [00:03, 1406.14 examples/s] Generating train split: 5256 examples [00:03, 1480.60 examples/s] Generating train split: 5424 examples [00:04, 1525.76 examples/s] Generating train split: 5615 examples [00:04, 1626.54 examples/s] Generating train split: 5847 examples [00:04, 1819.32 examples/s] Generating train split: 6096 examples [00:04, 1628.07 examples/s] Generating train split: 6318 examples [00:04, 1772.44 examples/s] Generating train split: 6511 examples [00:04, 1812.82 examples/s] Generating train split: 6751 examples [00:04, 1732.66 examples/s] Generating train split: 7000 examples [00:05, 1480.66 examples/s] Generating train split: 7170 examples [00:05, 1525.90 examples/s] Generating train split: 7335 examples [00:05, 1552.06 examples/s] Generating train split: 7520 examples [00:05, 1614.80 examples/s] Generating train split: 7698 examples [00:05, 1655.31 examples/s] Generating train split: 7949 examples [00:05, 1657.55 examples/s] Generating train split: 8177 examples [00:05, 1419.31 examples/s] Generating train split: 8352 examples [00:05, 1484.50 examples/s] Generating train split: 8512 examples [00:06, 1501.58 examples/s] Generating train split: 8729 examples [00:06, 1667.42 examples/s] Generating train split: 8910 examples [00:06, 1705.12 examples/s] Generating train split: 9165 examples [00:06, 1438.58 examples/s] Generating train split: 9330 examples [00:06, 1483.22 examples/s] Generating train split: 9501 examples [00:06, 1533.76 examples/s] Generating train split: 9668 examples [00:06, 1565.15 examples/s] Generating train split: 9880 examples [00:06, 1712.02 examples/s] Generating train split: 10074 examples [00:07, 1392.32 examples/s] Generating train split: 10320 examples [00:07, 1464.61 examples/s] Generating train split: 10484 examples [00:07, 1500.61 examples/s] Generating train split: 10706 examples [00:07, 1488.11 examples/s] Generating train split: 10890 examples [00:07, 1561.42 examples/s] Generating train split: 11088 examples [00:07, 1344.40 examples/s] Generating train split: 11272 examples [00:07, 1451.97 examples/s] Generating train split: 11444 examples [00:07, 1510.27 examples/s] Generating train split: 11637 examples [00:08, 1616.70 examples/s] Generating train split: 11810 examples [00:08, 1644.38 examples/s] Generating train split: 11996 examples [00:08, 1703.68 examples/s] Generating train split: 12185 examples [00:08, 1474.44 examples/s] Generating train split: 12353 examples [00:08, 1522.07 examples/s] Generating train split: 12557 examples [00:08, 1656.48 examples/s] Generating train split: 12739 examples [00:08, 1699.51 examples/s] Generating train split: 12918 examples [00:08, 1721.07 examples/s] Generating train split: 13182 examples [00:09, 1494.64 examples/s] Generating train split: 13355 examples [00:09, 1549.45 examples/s] Generating train split: 13579 examples [00:09, 1719.46 examples/s] Generating train split: 13672 examples [00:09, 1464.90 examples/s] | |
| Generating validation split | |
| topic_segmentation | |
| 06/19/2024 22:00:31 - INFO - datasets.builder - Generating validation split | |
| Generating validation split: 0 examples [00:00, ? examples/s] Generating validation split: 69 examples [00:00, 579.82 examples/s] Generating validation split: 218 examples [00:00, 1069.82 examples/s] Generating validation split: 373 examples [00:00, 1276.30 examples/s] Generating validation split: 520 examples [00:00, 1341.50 examples/s] Generating validation split: 703 examples [00:00, 1510.53 examples/s] Generating validation split: 881 examples [00:00, 1597.28 examples/s] Generating validation split: 1071 examples [00:00, 1270.73 examples/s] Generating validation split: 1274 examples [00:00, 1464.39 examples/s] Generating validation split: 1467 examples [00:01, 1587.66 examples/s] Generating validation split: 1713 examples [00:01, 1601.55 examples/s] Generating validation split: 1906 examples [00:01, 1677.42 examples/s] Generating validation split: 1950 examples [00:01, 1426.26 examples/s] | |
| Generating test split | |
| topic_segmentation | |
| 06/19/2024 22:00:32 - INFO - datasets.builder - Generating test split | |
| Generating test split: 0 examples [00:00, ? examples/s] Generating test split: 1 examples [00:00, 7.47 examples/s] Generating test split: 159 examples [00:00, 810.44 examples/s] Generating test split: 302 examples [00:00, 1066.26 examples/s] Generating test split: 477 examples [00:00, 1316.18 examples/s] Generating test split: 663 examples [00:00, 1501.87 examples/s] Generating test split: 826 examples [00:00, 1538.20 examples/s] Generating test split: 1000 examples [00:00, 1257.60 examples/s] Generating test split: 1151 examples [00:00, 1322.06 examples/s] Generating test split: 1322 examples [00:01, 1425.72 examples/s] Generating test split: 1495 examples [00:01, 1508.46 examples/s] Generating test split: 1683 examples [00:01, 1610.97 examples/s] Generating test split: 1891 examples [00:01, 1745.28 examples/s] Generating test split: 2077 examples [00:01, 1408.22 examples/s] Generating test split: 2256 examples [00:01, 1500.50 examples/s] Generating test split: 2427 examples [00:01, 1543.24 examples/s] Generating test split: 2619 examples [00:01, 1644.22 examples/s] Generating test split: 2837 examples [00:01, 1571.16 examples/s] Generating test split: 3071 examples [00:02, 1378.60 examples/s] Generating test split: 3265 examples [00:02, 1501.05 examples/s] Generating test split: 3458 examples [00:02, 1601.68 examples/s] Generating test split: 3718 examples [00:02, 1630.09 examples/s] Generating test split: 3897 examples [00:02, 1666.47 examples/s] Generating test split: 3904 examples [00:02, 1445.18 examples/s] | |
| Dataset wiki_section_city downloaded and prepared to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4. Subsequent calls will reuse this data. | |
| topic_segmentation | |
| 06/19/2024 22:00:35 - INFO - datasets.builder - Dataset wiki_section_city downloaded and prepared to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4. Subsequent calls will reuse this data. | |
| [INFO|configuration_utils.py:658] 2024-06-19 22:00:36,128 >> loading configuration file /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/config.json | |
| [INFO|configuration_utils.py:712] 2024-06-19 22:00:36,132 >> Model config BertConfig { | |
| "_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "architectures": [ | |
| "BertWithDAForSentenceLabelingTopicSegmentation" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "cache_dir": null, | |
| "cl_anchor_level": "eop_list", | |
| "cl_loss_weight": 0.5, | |
| "cl_negative_k": 3, | |
| "cl_positive_k": 1, | |
| "cl_temp": 0.1, | |
| "classifier_dropout": null, | |
| "config_name": null, | |
| "directionality": "bidi", | |
| "do_cssl": true, | |
| "do_da_ts": true, | |
| "do_tssp": true, | |
| "finetuning_task": "topic_segment", | |
| "focal_loss_gamma": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "B-EOP", | |
| "1": "O" | |
| }, | |
| "ignore_mismatched_sizes": false, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "B-EOP": 0, | |
| "O": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_name_or_path": "neuralmind/bert-large-portuguese-cased", | |
| "model_revision": "main", | |
| "model_type": "bert", | |
| "num_attention_heads": 16, | |
| "num_gpu": 1, | |
| "num_hidden_layers": 24, | |
| "num_topic_labels": 0, | |
| "num_tssp_labels": 3, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "sentence_pooler_type": null, | |
| "tokenizer_name": null, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.0", | |
| "ts_loss_weight": 1.0, | |
| "ts_score_predictor": "lt", | |
| "ts_score_predictor_cos_temp": 1, | |
| "tssp_ablation": "none", | |
| "tssp_loss_weight": 1.0, | |
| "type_vocab_size": 2, | |
| "use_auth_token": false, | |
| "use_cache": true, | |
| "vocab_size": 29795, | |
| "weight_label_zero": 0.5 | |
| } | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:00:36,145 >> loading file vocab.txt | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:00:36,145 >> loading file tokenizer.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:00:36,145 >> loading file added_tokens.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:00:36,145 >> loading file special_tokens_map.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:00:36,145 >> loading file tokenizer_config.json | |
| [INFO|modeling_utils.py:2272] 2024-06-19 22:00:36,225 >> loading weights file /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/pytorch_model.bin | |
| [INFO|modeling_utils.py:2857] 2024-06-19 22:01:00,370 >> All model checkpoint weights were used when initializing BertWithDAForSentenceLabelingTopicSegmentation. | |
| [INFO|modeling_utils.py:2865] 2024-06-19 22:01:00,370 >> All the weights of BertWithDAForSentenceLabelingTopicSegmentation were initialized from the model checkpoint at /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41. | |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use BertWithDAForSentenceLabelingTopicSegmentation for predictions without further training. | |
| Process #0 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| labels_are_int: False | |
| label_to_id: {'B-EOP': 0, 'O': 1} | |
| config: BertConfig { | |
| "_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "architectures": [ | |
| "BertWithDAForSentenceLabelingTopicSegmentation" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "cache_dir": null, | |
| "cl_anchor_level": "eop_matrix", | |
| "cl_loss_weight": 0.0, | |
| "cl_negative_k": 1, | |
| "cl_positive_k": 1, | |
| "cl_temp": 1, | |
| "classifier_dropout": null, | |
| "config_name": null, | |
| "directionality": "bidi", | |
| "do_cssl": false, | |
| "do_da_ts": false, | |
| "do_tssp": false, | |
| "finetuning_task": "topic_segment", | |
| "focal_loss_gamma": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "B-EOP", | |
| "1": "O" | |
| }, | |
| "ignore_mismatched_sizes": false, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "B-EOP": 0, | |
| "O": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "model_revision": "main", | |
| "model_type": "bert", | |
| "num_attention_heads": 16, | |
| "num_gpu": 1, | |
| "num_hidden_layers": 24, | |
| "num_topic_labels": 0, | |
| "num_tssp_labels": 3, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "sentence_pooler_type": null, | |
| "tokenizer_name": null, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.0", | |
| "ts_loss_weight": 1.0, | |
| "ts_score_predictor": "lt", | |
| "ts_score_predictor_cos_temp": 1, | |
| "tssp_ablation": "none", | |
| "tssp_loss_weight": 0.0, | |
| "type_vocab_size": 2, | |
| "use_auth_token": false, | |
| "use_cache": true, | |
| "vocab_size": 29795, | |
| "weight_label_zero": 0.5 | |
| } | |
| model_type: bert | |
| final max_seq_length: 512 | |
| label_list: ['B-EOP', 'O'] | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Process #0 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| Process #1 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Process #1 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| Process #2 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Process #2 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| Process #3 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Process #3 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| Process #4 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Process #4 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| Spawning 5 processes | |
| 06/19/2024 22:01:00 - INFO - datasets.arrow_dataset - Spawning 5 processes | |
| Running tokenizer on prediction dataset (num_proc=5): 0%| | 0/3904 [00:00<?, ? examples/s] Running tokenizer on prediction dataset (num_proc=5): 0%| | 0/3904 [00:08<?, ? examples/s] | |
| 0 | |
| 06/19/2024 22:01:19 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False | |
| 06/19/2024 22:01:19 - INFO - __main__ - Training/evaluation parameters TrainingArguments( | |
| _n_gpu=1, | |
| adafactor=False, | |
| adam_beta1=0.9, | |
| adam_beta2=0.999, | |
| adam_epsilon=1e-08, | |
| auto_find_batch_size=False, | |
| bf16=False, | |
| bf16_full_eval=False, | |
| data_seed=None, | |
| dataloader_drop_last=False, | |
| dataloader_num_workers=0, | |
| dataloader_pin_memory=True, | |
| ddp_bucket_cap_mb=None, | |
| ddp_find_unused_parameters=None, | |
| ddp_timeout=1800, | |
| debug=[], | |
| deepspeed=None, | |
| disable_tqdm=False, | |
| do_eval=False, | |
| do_predict=True, | |
| do_train=False, | |
| eval_accumulation_steps=None, | |
| eval_delay=0, | |
| eval_steps=None, | |
| evaluation_strategy=no, | |
| fp16=False, | |
| fp16_backend=auto, | |
| fp16_full_eval=False, | |
| fp16_opt_level=O1, | |
| fsdp=[], | |
| fsdp_min_num_params=0, | |
| fsdp_transformer_layer_cls_to_wrap=None, | |
| full_determinism=False, | |
| gradient_accumulation_steps=1, | |
| gradient_checkpointing=False, | |
| greater_is_better=None, | |
| group_by_length=False, | |
| half_precision_backend=auto, | |
| 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, | |
| 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=False, | |
| local_rank=-1, | |
| log_level=passive, | |
| log_level_replica=passive, | |
| log_on_each_node=True, | |
| logging_dir=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/runs/Jun19_22-01-19_ppi-nlp6, | |
| logging_first_step=False, | |
| logging_nan_inf_filter=True, | |
| logging_steps=500, | |
| logging_strategy=steps, | |
| lr_scheduler_type=linear, | |
| max_grad_norm=1.0, | |
| max_steps=-1, | |
| metric_for_best_model=None, | |
| mp_parameters=, | |
| no_cuda=False, | |
| num_train_epochs=3.0, | |
| optim=adamw_hf, | |
| optim_args=None, | |
| output_dir=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41, | |
| overwrite_output_dir=False, | |
| past_index=-1, | |
| per_device_eval_batch_size=4, | |
| per_device_train_batch_size=8, | |
| prediction_loss_only=False, | |
| push_to_hub=False, | |
| 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=[], | |
| resume_from_checkpoint=None, | |
| run_name=/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41, | |
| save_on_each_node=False, | |
| save_steps=500, | |
| save_strategy=steps, | |
| save_total_limit=None, | |
| seed=42, | |
| sharded_ddp=[], | |
| skip_memory_metrics=True, | |
| tf32=None, | |
| torch_compile=False, | |
| torch_compile_backend=None, | |
| torch_compile_mode=None, | |
| torchdynamo=None, | |
| tpu_metrics_debug=False, | |
| tpu_num_cores=None, | |
| use_ipex=False, | |
| use_legacy_prediction_loop=False, | |
| use_mps_device=False, | |
| warmup_ratio=0.0, | |
| warmup_steps=0, | |
| weight_decay=0.0, | |
| xpu_backend=None, | |
| ) | |
| /home/ext_maiara_frodrigues2000_gmail_/.pyenv/versions/spokennlp/lib/python3.8/site-packages/datasets/load.py:2555: FutureWarning: 'ignore_verifications' was deprecated in favor of 'verification_mode' in version 2.9.1 and will be removed in 3.0.0. | |
| You can remove this warning by passing 'verification_mode=no_checks' instead. | |
| warnings.warn( | |
| /home/ext_maiara_frodrigues2000_gmail_/.pyenv/versions/spokennlp/lib/python3.8/site-packages/datasets/load.py:929: FutureWarning: The repository for wiki_section_city contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at ./src/datasets/wiki_section_city/wiki_section_city.py | |
| You can avoid this message in future by passing the argument `trust_remote_code=True`. | |
| Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`. | |
| warnings.warn( | |
| No config specified, defaulting to the single config: wiki_section_city/WikiSectionCityForDocumentSegmentation | |
| 06/19/2024 22:01:19 - INFO - datasets.builder - No config specified, defaulting to the single config: wiki_section_city/WikiSectionCityForDocumentSegmentation | |
| Using custom data configuration WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad | |
| 06/19/2024 22:01:19 - INFO - datasets.builder - Using custom data configuration WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad | |
| Loading Dataset Infos from /home/ext_luti4497_gmail_com/.cache/huggingface/modules/datasets_modules/datasets/wiki_section_city/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4 | |
| 06/19/2024 22:01:19 - INFO - datasets.info - Loading Dataset Infos from /home/ext_luti4497_gmail_com/.cache/huggingface/modules/datasets_modules/datasets/wiki_section_city/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4 | |
| Generating dataset wiki_section_city (/projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4) | |
| 06/19/2024 22:01:19 - INFO - datasets.builder - Generating dataset wiki_section_city (/projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4) | |
| Downloading and preparing dataset wiki_section_city/WikiSectionCityForDocumentSegmentation to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4... | |
| 06/19/2024 22:01:19 - INFO - datasets.builder - Downloading and preparing dataset wiki_section_city/WikiSectionCityForDocumentSegmentation to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4... | |
| Downloading took 0.0 min | |
| 06/19/2024 22:01:19 - INFO - datasets.download.download_manager - Downloading took 0.0 min | |
| Checksum Computation took 0.0 min | |
| 06/19/2024 22:01:19 - INFO - datasets.download.download_manager - Checksum Computation took 0.0 min | |
| Generating train split | |
| 06/19/2024 22:01:19 - INFO - datasets.builder - Generating train split | |
| Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 1 examples [00:00, 1.86 examples/s] Generating train split: 164 examples [00:00, 344.11 examples/s] Generating train split: 327 examples [00:00, 640.15 examples/s] Generating train split: 487 examples [00:00, 873.61 examples/s] Generating train split: 676 examples [00:00, 1135.01 examples/s] Generating train split: 865 examples [00:01, 1332.98 examples/s] Generating train split: 1085 examples [00:01, 1203.80 examples/s] Generating train split: 1249 examples [00:01, 1302.58 examples/s] Generating train split: 1444 examples [00:01, 1462.41 examples/s] Generating train split: 1623 examples [00:01, 1548.04 examples/s] Generating train split: 1873 examples [00:01, 1581.85 examples/s] Generating train split: 2088 examples [00:01, 1354.26 examples/s] Generating train split: 2312 examples [00:02, 1394.05 examples/s] Generating train split: 2488 examples [00:02, 1474.50 examples/s] Generating train split: 2715 examples [00:02, 1477.61 examples/s] Generating train split: 2901 examples [00:02, 1564.50 examples/s] Generating train split: 3075 examples [00:02, 1305.09 examples/s] Generating train split: 3244 examples [00:02, 1387.65 examples/s] Generating train split: 3439 examples [00:02, 1520.39 examples/s] Generating train split: 3612 examples [00:02, 1573.60 examples/s] Generating train split: 3783 examples [00:03, 1607.63 examples/s] Generating train split: 4000 examples [00:03, 1339.28 examples/s] Generating train split: 4170 examples [00:03, 1418.57 examples/s] Generating train split: 4362 examples [00:03, 1541.76 examples/s] Generating train split: 4561 examples [00:03, 1657.36 examples/s] Generating train split: 4740 examples [00:03, 1670.80 examples/s] Generating train split: 4920 examples [00:03, 1704.66 examples/s] Generating train split: 5191 examples [00:03, 1556.63 examples/s] Generating train split: 5381 examples [00:04, 1638.00 examples/s] Generating train split: 5553 examples [00:04, 1658.23 examples/s] Generating train split: 5781 examples [00:04, 1823.54 examples/s] Generating train split: 5979 examples [00:04, 1854.55 examples/s] Generating train split: 6222 examples [00:04, 1685.10 examples/s] Generating train split: 6410 examples [00:04, 1721.16 examples/s] Generating train split: 6649 examples [00:04, 1673.17 examples/s] Generating train split: 6887 examples [00:04, 1638.36 examples/s] Generating train split: 7083 examples [00:05, 1427.36 examples/s] Generating train split: 7245 examples [00:05, 1469.27 examples/s] Generating train split: 7409 examples [00:05, 1508.98 examples/s] Generating train split: 7593 examples [00:05, 1584.40 examples/s] Generating train split: 7762 examples [00:05, 1609.11 examples/s] Generating train split: 7937 examples [00:05, 1641.42 examples/s] Generating train split: 8168 examples [00:05, 1348.83 examples/s] Generating train split: 8322 examples [00:05, 1391.53 examples/s] Generating train split: 8551 examples [00:06, 1432.31 examples/s] Generating train split: 8771 examples [00:06, 1602.43 examples/s] Generating train split: 8952 examples [00:06, 1646.20 examples/s] Generating train split: 9160 examples [00:06, 1403.59 examples/s] Generating train split: 9318 examples [00:06, 1438.63 examples/s] Generating train split: 9489 examples [00:06, 1503.82 examples/s] Generating train split: 9651 examples [00:06, 1526.44 examples/s] Generating train split: 9857 examples [00:06, 1665.31 examples/s] Generating train split: 10070 examples [00:07, 1373.33 examples/s] Generating train split: 10315 examples [00:07, 1442.57 examples/s] Generating train split: 10479 examples [00:07, 1485.39 examples/s] Generating train split: 10704 examples [00:07, 1483.83 examples/s] Generating train split: 10894 examples [00:07, 1577.27 examples/s] Generating train split: 11092 examples [00:07, 1361.95 examples/s] Generating train split: 11277 examples [00:07, 1468.39 examples/s] Generating train split: 11445 examples [00:08, 1516.88 examples/s] Generating train split: 11632 examples [00:08, 1600.38 examples/s] Generating train split: 11807 examples [00:08, 1633.90 examples/s] Generating train split: 11993 examples [00:08, 1693.04 examples/s] Generating train split: 12178 examples [00:08, 1428.25 examples/s] Generating train split: 12338 examples [00:08, 1445.53 examples/s] Generating train split: 12543 examples [00:08, 1600.38 examples/s] Generating train split: 12734 examples [00:08, 1673.56 examples/s] Generating train split: 12919 examples [00:08, 1718.61 examples/s] Generating train split: 13173 examples [00:09, 1473.04 examples/s] Generating train split: 13349 examples [00:09, 1539.35 examples/s] Generating train split: 13549 examples [00:09, 1642.87 examples/s] Generating train split: 13672 examples [00:09, 1454.41 examples/s] | |
| Generating validation split | |
| topic_segmentation | |
| 06/19/2024 22:01:28 - INFO - datasets.builder - Generating validation split | |
| Generating validation split: 0 examples [00:00, ? examples/s] Generating validation split: 69 examples [00:00, 608.54 examples/s] Generating validation split: 217 examples [00:00, 1089.66 examples/s] Generating validation split: 367 examples [00:00, 1264.36 examples/s] Generating validation split: 524 examples [00:00, 1378.19 examples/s] Generating validation split: 703 examples [00:00, 1519.31 examples/s] Generating validation split: 869 examples [00:00, 1565.22 examples/s] Generating validation split: 1068 examples [00:00, 1252.69 examples/s] Generating validation split: 1271 examples [00:00, 1448.10 examples/s] Generating validation split: 1464 examples [00:01, 1575.39 examples/s] Generating validation split: 1713 examples [00:01, 1595.15 examples/s] Generating validation split: 1906 examples [00:01, 1673.40 examples/s] Generating validation split: 1950 examples [00:01, 1431.59 examples/s] | |
| Generating test split | |
| topic_segmentation | |
| 06/19/2024 22:01:30 - INFO - datasets.builder - Generating test split | |
| Generating test split: 0 examples [00:00, ? examples/s] Generating test split: 1 examples [00:00, 8.19 examples/s] Generating test split: 155 examples [00:00, 825.12 examples/s] Generating test split: 295 examples [00:00, 1071.91 examples/s] Generating test split: 465 examples [00:00, 1308.99 examples/s] Generating test split: 648 examples [00:00, 1489.93 examples/s] Generating test split: 814 examples [00:00, 1542.01 examples/s] Generating test split: 986 examples [00:00, 1591.45 examples/s] Generating test split: 1152 examples [00:00, 1267.31 examples/s] Generating test split: 1321 examples [00:01, 1376.15 examples/s] Generating test split: 1495 examples [00:01, 1471.51 examples/s] Generating test split: 1682 examples [00:01, 1579.17 examples/s] Generating test split: 1882 examples [00:01, 1693.42 examples/s] Generating test split: 2077 examples [00:01, 1402.70 examples/s] Generating test split: 2257 examples [00:01, 1499.42 examples/s] Generating test split: 2425 examples [00:01, 1540.54 examples/s] Generating test split: 2609 examples [00:01, 1616.79 examples/s] Generating test split: 2835 examples [00:01, 1568.50 examples/s] Generating test split: 3000 examples [00:02, 1364.80 examples/s] Generating test split: 3162 examples [00:02, 1425.57 examples/s] Generating test split: 3367 examples [00:02, 1584.11 examples/s] Generating test split: 3589 examples [00:02, 1523.09 examples/s] Generating test split: 3752 examples [00:02, 1546.15 examples/s] Generating test split: 3904 examples [00:02, 1420.90 examples/s] | |
| Dataset wiki_section_city downloaded and prepared to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4. Subsequent calls will reuse this data. | |
| topic_segmentation | |
| 06/19/2024 22:01:32 - INFO - datasets.builder - Dataset wiki_section_city downloaded and prepared to /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4. Subsequent calls will reuse this data. | |
| [INFO|configuration_utils.py:658] 2024-06-19 22:01:33,637 >> loading configuration file /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/config.json | |
| [INFO|configuration_utils.py:712] 2024-06-19 22:01:33,641 >> Model config BertConfig { | |
| "_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "architectures": [ | |
| "BertWithDAForSentenceLabelingTopicSegmentation" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "cache_dir": null, | |
| "cl_anchor_level": "eop_list", | |
| "cl_loss_weight": 0.5, | |
| "cl_negative_k": 3, | |
| "cl_positive_k": 1, | |
| "cl_temp": 0.1, | |
| "classifier_dropout": null, | |
| "config_name": null, | |
| "directionality": "bidi", | |
| "do_cssl": true, | |
| "do_da_ts": true, | |
| "do_tssp": true, | |
| "finetuning_task": "topic_segment", | |
| "focal_loss_gamma": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "B-EOP", | |
| "1": "O" | |
| }, | |
| "ignore_mismatched_sizes": false, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "B-EOP": 0, | |
| "O": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_name_or_path": "neuralmind/bert-large-portuguese-cased", | |
| "model_revision": "main", | |
| "model_type": "bert", | |
| "num_attention_heads": 16, | |
| "num_gpu": 1, | |
| "num_hidden_layers": 24, | |
| "num_topic_labels": 0, | |
| "num_tssp_labels": 3, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "sentence_pooler_type": null, | |
| "tokenizer_name": null, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.0", | |
| "ts_loss_weight": 1.0, | |
| "ts_score_predictor": "lt", | |
| "ts_score_predictor_cos_temp": 1, | |
| "tssp_ablation": "none", | |
| "tssp_loss_weight": 1.0, | |
| "type_vocab_size": 2, | |
| "use_auth_token": false, | |
| "use_cache": true, | |
| "vocab_size": 29795, | |
| "weight_label_zero": 0.5 | |
| } | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:01:33,643 >> loading file vocab.txt | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:01:33,643 >> loading file tokenizer.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:01:33,643 >> loading file added_tokens.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:01:33,643 >> loading file special_tokens_map.json | |
| [INFO|tokenization_utils_base.py:1800] 2024-06-19 22:01:33,643 >> loading file tokenizer_config.json | |
| [INFO|modeling_utils.py:2272] 2024-06-19 22:01:33,668 >> loading weights file /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41/pytorch_model.bin | |
| [INFO|modeling_utils.py:2857] 2024-06-19 22:01:37,435 >> All model checkpoint weights were used when initializing BertWithDAForSentenceLabelingTopicSegmentation. | |
| [INFO|modeling_utils.py:2865] 2024-06-19 22:01:37,436 >> All the weights of BertWithDAForSentenceLabelingTopicSegmentation were initialized from the model checkpoint at /projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41. | |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use BertWithDAForSentenceLabelingTopicSegmentation for predictions without further training. | |
| Process #0 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| labels_are_int: False | |
| label_to_id: {'B-EOP': 0, 'O': 1} | |
| config: BertConfig { | |
| "_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "architectures": [ | |
| "BertWithDAForSentenceLabelingTopicSegmentation" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "cache_dir": null, | |
| "cl_anchor_level": "eop_matrix", | |
| "cl_loss_weight": 0.0, | |
| "cl_negative_k": 1, | |
| "cl_positive_k": 1, | |
| "cl_temp": 1, | |
| "classifier_dropout": null, | |
| "config_name": null, | |
| "directionality": "bidi", | |
| "do_cssl": false, | |
| "do_da_ts": false, | |
| "do_tssp": false, | |
| "finetuning_task": "topic_segment", | |
| "focal_loss_gamma": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "B-EOP", | |
| "1": "O" | |
| }, | |
| "ignore_mismatched_sizes": false, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "B-EOP": 0, | |
| "O": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_name_or_path": "/projeto/SpokenNLP/emnlp2023-topic_segmentation/output/neuralmind/bert-large-portuguese-cased-finetune-wiki_section_disease/seed42-seq512-lr5e-05-epoch5-bs4-ts1.0-tssp1.0-cl0.5-2024-05-30_21:01:41", | |
| "model_revision": "main", | |
| "model_type": "bert", | |
| "num_attention_heads": 16, | |
| "num_gpu": 1, | |
| "num_hidden_layers": 24, | |
| "num_topic_labels": 0, | |
| "num_tssp_labels": 3, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "sentence_pooler_type": null, | |
| "tokenizer_name": null, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.0", | |
| "ts_loss_weight": 1.0, | |
| "ts_score_predictor": "lt", | |
| "ts_score_predictor_cos_temp": 1, | |
| "tssp_ablation": "none", | |
| "tssp_loss_weight": 0.0, | |
| "type_vocab_size": 2, | |
| "use_auth_token": false, | |
| "use_cache": true, | |
| "vocab_size": 29795, | |
| "weight_label_zero": 0.5 | |
| } | |
| model_type: bert | |
| final max_seq_length: 512 | |
| label_list: ['B-EOP', 'O'] | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Process #0 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| Process #1 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Process #1 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| Process #2 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Process #2 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| Process #3 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Process #3 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| Process #4 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Process #4 will write at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| Spawning 5 processes | |
| 06/19/2024 22:01:37 - INFO - datasets.arrow_dataset - Spawning 5 processes | |
| Running tokenizer on prediction dataset (num_proc=5): 0%| | 0/3904 [00:00<?, ? examples/s]Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| 06/19/2024 22:01:58 - INFO - datasets.arrow_dataset - Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00004_of_00005.arrow | |
| Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| 06/19/2024 22:01:59 - INFO - datasets.arrow_dataset - Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00002_of_00005.arrow | |
| Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| 06/19/2024 22:02:00 - INFO - datasets.arrow_dataset - Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00001_of_00005.arrow | |
| Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| 06/19/2024 22:02:00 - INFO - datasets.arrow_dataset - Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00003_of_00005.arrow | |
| Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| 06/19/2024 22:02:01 - INFO - datasets.arrow_dataset - Caching processed dataset at /projeto/SpokenNLP/emnlp2023-topic_segmentation/cached_data/wiki_section_city_neuralmind/bert-large-portuguese-cased_512/wiki_section_city/WikiSectionCityForDocumentSegmentation-15c5ff72c77600ad/1.1.1/cafcd4e7f86f04cfd46e90d782f42526ea3b1d6deab48ae6dcf7f4bab4f252d4/cache-bert_wiki_section_city_512_test_00000_of_00005.arrow | |
| Running tokenizer on prediction dataset (num_proc=5): 20%|█▉ | 780/3904 [00:31<02:05, 24.91 examples/s] Running tokenizer on prediction dataset (num_proc=5): 60%|█████▉ | 2342/3904 [00:32<00:16, 92.11 examples/s] Running tokenizer on prediction dataset (num_proc=5): 80%|███████▉ | 3123/3904 [00:32<00:05, 136.98 examples/s] Running tokenizer on prediction dataset (num_proc=5): 100%|██████████| 3904/3904 [00:33<00:00, 193.46 examples/s] Running tokenizer on prediction dataset (num_proc=5): 100%|██████████| 3904/3904 [00:38<00:00, 101.32 examples/s] | |
| Concatenating 5 shards | |
| 06/19/2024 22:02:16 - INFO - datasets.arrow_dataset - Concatenating 5 shards | |
| 06/19/2024 22:02:19 - INFO - __main__ - *** Predict test set *** | |
| ./src/ts_sentence_seq_labeling.py:1017: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate | |
| metric = load_metric(data_args.metric_name) | |
| /home/ext_maiara_frodrigues2000_gmail_/.pyenv/versions/spokennlp/lib/python3.8/site-packages/datasets/load.py:855: FutureWarning: The repository for seqeval contains custom code which must be executed to correctly load the metric. You can inspect the repository content at ./src/metrics/seqeval.py | |
| You can avoid this message in future by passing the argument `trust_remote_code=True`. | |
| Passing `trust_remote_code=True` will be mandatory to load this metric from the next major release of `datasets`. | |
| warnings.warn( | |
| [INFO|trainer.py:710] 2024-06-19 22:02:21,579 >> The following columns in the test set don't have a corresponding argument in `BertWithDAForSentenceLabelingTopicSegmentation.forward` and have been ignored: sentences, example_id. If sentences, example_id are not expected by `BertWithDAForSentenceLabelingTopicSegmentation.forward`, you can safely ignore this message. | |
| [INFO|trainer.py:2964] 2024-06-19 22:02:21,586 >> ***** Running Prediction ***** | |
| [INFO|trainer.py:2966] 2024-06-19 22:02:21,586 >> Num examples = 15271 | |
| [INFO|trainer.py:2969] 2024-06-19 22:02:21,586 >> Batch size = 4 | |
| num predict samples: 15271 | |
| num predict examples: 3904 | |
| 0%| | 0/3818 [00:00<?, ?it/s] 0%| | 2/3818 [00:00<12:30, 5.08it/s] 0%| | 3/3818 [00:00<17:54, 3.55it/s] 0%| | 4/3818 [00:01<20:32, 3.09it/s] 0%| | 5/3818 [00:01<22:04, 2.88it/s] 0%| | 6/3818 [00:01<23:08, 2.74it/s] 0%| | 7/3818 [00:02<23:44, 2.68it/s] 0%| | 8/3818 [00:02<24:11, 2.63it/s] 0%| | 9/3818 [00:03<24:28, 2.59it/s] 0%| | 10/3818 [00:03<24:36, 2.58it/s] 0%| | 11/3818 [00:03<24:46, 2.56it/s] 0%| | 12/3818 [00:04<24:55, 2.54it/s] 0%| | 13/3818 [00:04<24:59, 2.54it/s] 0%| | 14/3818 [00:05<25:07, 2.52it/s] 0%| | 15/3818 [00:05<25:08, 2.52it/s] 0%| | 16/3818 [00:05<25:07, 2.52it/s] 0%| | 17/3818 [00:06<25:14, 2.51it/s] 0%| | 18/3818 [00:06<25:11, 2.51it/s] 0%| | 19/3818 [00:07<25:13, 2.51it/s] 1%| | 20/3818 [00:07<25:15, 2.51it/s] 1%| | 21/3818 [00:07<25:13, 2.51it/s] 1%| | 22/3818 [00:08<25:10, 2.51it/s] 1%| | 23/3818 [00:08<25:17, 2.50it/s] 1%| | 24/3818 [00:09<25:18, 2.50it/s] 1%| | 25/3818 [00:09<25:19, 2.50it/s] 1%| | 26/3818 [00:09<25:21, 2.49it/s] 1%| | 27/3818 [00:10<25:17, 2.50it/s] 1%| | 28/3818 [00:10<25:19, 2.49it/s] 1%| | 29/3818 [00:11<25:21, 2.49it/s] 1%| | 30/3818 [00:11<25:18, 2.49it/s] 1%| | 31/3818 [00:11<25:18, 2.49it/s] 1%| | 32/3818 [00:12<25:21, 2.49it/s] 1%| | 33/3818 [00:12<25:20, 2.49it/s] 1%| | 34/3818 [00:13<25:16, 2.49it/s] 1%| | 35/3818 [00:13<25:17, 2.49it/s] 1%| | 36/3818 [00:13<25:25, 2.48it/s] 1%| | 37/3818 [00:14<25:23, 2.48it/s] 1%| | 38/3818 [00:14<25:25, 2.48it/s] 1%| | 39/3818 [00:15<25:24, 2.48it/s] 1%| | 40/3818 [00:15<25:23, 2.48it/s] 1%| | 41/3818 [00:15<25:26, 2.47it/s] 1%| | 42/3818 [00:16<25:25, 2.47it/s] 1%| | 43/3818 [00:16<25:27, 2.47it/s] 1%| | 44/3818 [00:17<25:25, 2.47it/s] 1%| | 45/3818 [00:17<25:25, 2.47it/s] 1%| | 46/3818 [00:18<25:30, 2.46it/s] 1%| | 47/3818 [00:18<25:25, 2.47it/s] 1%|▏ | 48/3818 [00:18<25:25, 2.47it/s] 1%|▏ | 49/3818 [00:19<25:26, 2.47it/s] 1%|▏ | 50/3818 [00:19<25:22, 2.47it/s] 1%|▏ | 51/3818 [00:20<25:27, 2.47it/s] 1%|▏ | 52/3818 [00:20<25:27, 2.46it/s] 1%|▏ | 53/3818 [00:20<25:28, 2.46it/s] 1%|▏ | 54/3818 [00:21<25:22, 2.47it/s] 1%|▏ | 55/3818 [00:21<25:19, 2.48it/s] 1%|▏ | 56/3818 [00:22<25:19, 2.48it/s] 1%|▏ | 57/3818 [00:22<25:18, 2.48it/s] 2%|▏ | 58/3818 [00:22<25:18, 2.48it/s] 2%|▏ | 59/3818 [00:23<25:19, 2.47it/s] 2%|▏ | 60/3818 [00:23<25:19, 2.47it/s] 2%|▏ | 61/3818 [00:24<25:18, 2.47it/s] 2%|▏ | 62/3818 [00:24<25:21, 2.47it/s] 2%|▏ | 63/3818 [00:24<25:22, 2.47it/s] 2%|▏ | 64/3818 [00:25<25:20, 2.47it/s] 2%|▏ | 65/3818 [00:25<25:21, 2.47it/s] 2%|▏ | 66/3818 [00:26<25:17, 2.47it/s] 2%|▏ | 67/3818 [00:26<25:19, 2.47it/s] 2%|▏ | 68/3818 [00:26<25:18, 2.47it/s] 2%|▏ | 69/3818 [00:27<25:13, 2.48it/s] 2%|▏ | 70/3818 [00:27<25:19, 2.47it/s] 2%|▏ | 71/3818 [00:28<25:20, 2.46it/s] 2%|▏ | 72/3818 [00:28<25:19, 2.46it/s] 2%|▏ | 73/3818 [00:28<25:27, 2.45it/s] 2%|▏ | 74/3818 [00:29<25:23, 2.46it/s] 2%|▏ | 75/3818 [00:29<25:25, 2.45it/s] 2%|▏ | 76/3818 [00:30<25:23, 2.46it/s] 2%|▏ | 77/3818 [00:30<25:18, 2.46it/s] 2%|▏ | 78/3818 [00:30<25:21, 2.46it/s] 2%|▏ | 79/3818 [00:31<25:19, 2.46it/s] 2%|▏ | 80/3818 [00:31<25:24, 2.45it/s] 2%|▏ | 81/3818 [00:32<25:24, 2.45it/s] 2%|▏ | 82/3818 [00:32<25:24, 2.45it/s] 2%|▏ | 83/3818 [00:33<25:24, 2.45it/s] 2%|▏ | 84/3818 [00:33<25:20, 2.46it/s] 2%|▏ | 85/3818 [00:33<25:20, 2.45it/s] 2%|▏ | 86/3818 [00:34<25:24, 2.45it/s] 2%|▏ | 87/3818 [00:34<25:25, 2.45it/s] 2%|▏ | 88/3818 [00:35<25:26, 2.44it/s] 2%|▏ | 89/3818 [00:35<25:26, 2.44it/s] 2%|▏ | 90/3818 [00:35<25:28, 2.44it/s] 2%|▏ | 91/3818 [00:36<25:28, 2.44it/s] 2%|▏ | 92/3818 [00:36<25:26, 2.44it/s] 2%|▏ | 93/3818 [00:37<25:27, 2.44it/s] 2%|▏ | 94/3818 [00:37<25:25, 2.44it/s] 2%|▏ | 95/3818 [00:37<25:28, 2.44it/s] 3%|▎ | 96/3818 [00:38<25:31, 2.43it/s] 3%|▎ | 97/3818 [00:38<25:37, 2.42it/s] 3%|▎ | 98/3818 [00:39<25:35, 2.42it/s] 3%|▎ | 99/3818 [00:39<25:32, 2.43it/s] 3%|▎ | 100/3818 [00:40<25:28, 2.43it/s] 3%|▎ | 101/3818 [00:40<25:33, 2.42it/s] 3%|▎ | 102/3818 [00:40<25:30, 2.43it/s] 3%|▎ | 103/3818 [00:41<25:25, 2.44it/s] 3%|▎ | 104/3818 [00:41<25:26, 2.43it/s] 3%|▎ | 105/3818 [00:42<25:27, 2.43it/s] 3%|▎ | 106/3818 [00:42<25:24, 2.44it/s] 3%|▎ | 107/3818 [00:42<25:30, 2.43it/s] 3%|▎ | 108/3818 [00:43<25:27, 2.43it/s] 3%|▎ | 109/3818 [00:43<25:29, 2.43it/s] 3%|▎ | 110/3818 [00:44<25:29, 2.42it/s] 3%|▎ | 111/3818 [00:44<25:28, 2.42it/s] 3%|▎ | 112/3818 [00:44<25:33, 2.42it/s] 3%|▎ | 113/3818 [00:45<25:30, 2.42it/s] 3%|▎ | 114/3818 [00:45<25:25, 2.43it/s] 3%|▎ | 115/3818 [00:46<25:30, 2.42it/s] 3%|▎ | 116/3818 [00:46<25:30, 2.42it/s] 3%|▎ | 117/3818 [00:47<25:34, 2.41it/s] 3%|▎ | 118/3818 [00:47<25:34, 2.41it/s] 3%|▎ | 119/3818 [00:47<25:33, 2.41it/s] 3%|▎ | 120/3818 [00:48<25:36, 2.41it/s] 3%|▎ | 121/3818 [00:48<25:30, 2.42it/s] 3%|▎ | 122/3818 [00:49<25:31, 2.41it/s] 3%|▎ | 123/3818 [00:49<25:32, 2.41it/s] 3%|▎ | 124/3818 [00:49<25:30, 2.41it/s] 3%|▎ | 125/3818 [00:50<25:32, 2.41it/s] 3%|▎ | 126/3818 [00:50<25:29, 2.41it/s] 3%|▎ | 127/3818 [00:51<25:35, 2.40it/s] 3%|▎ | 128/3818 [00:51<25:33, 2.41it/s] 3%|▎ | 129/3818 [00:52<25:35, 2.40it/s] 3%|▎ | 130/3818 [00:52<25:34, 2.40it/s] 3%|▎ | 131/3818 [00:52<25:36, 2.40it/s] 3%|▎ | 132/3818 [00:53<25:39, 2.39it/s] 3%|▎ | 133/3818 [00:53<25:36, 2.40it/s] 4%|▎ | 134/3818 [00:54<25:42, 2.39it/s] 4%|▎ | 135/3818 [00:54<25:39, 2.39it/s] 4%|▎ | 136/3818 [00:54<25:41, 2.39it/s] 4%|▎ | 137/3818 [00:55<25:39, 2.39it/s] 4%|▎ | 138/3818 [00:55<25:38, 2.39it/s] 4%|▎ | 139/3818 [00:56<25:40, 2.39it/s] 4%|▎ | 140/3818 [00:56<25:39, 2.39it/s] 4%|▎ | 141/3818 [00:57<25:36, 2.39it/s] 4%|▎ | 142/3818 [00:57<25:40, 2.39it/s] 4%|▎ | 143/3818 [00:57<25:42, 2.38it/s] 4%|▍ | 144/3818 [00:58<25:40, 2.38it/s] 4%|▍ | 145/3818 [00:58<25:36, 2.39it/s] 4%|▍ | 146/3818 [00:59<25:37, 2.39it/s] 4%|▍ | 147/3818 [00:59<25:39, 2.38it/s] 4%|▍ | 148/3818 [00:59<25:41, 2.38it/s] 4%|▍ | 149/3818 [01:00<25:40, 2.38it/s] 4%|▍ | 150/3818 [01:00<25:40, 2.38it/s] 4%|▍ | 151/3818 [01:01<25:41, 2.38it/s] 4%|▍ | 152/3818 [01:01<25:42, 2.38it/s] 4%|▍ | 153/3818 [01:02<25:43, 2.38it/s] 4%|▍ | 154/3818 [01:02<25:41, 2.38it/s] 4%|▍ | 155/3818 [01:02<25:42, 2.38it/s] 4%|▍ | 156/3818 [01:03<25:37, 2.38it/s] 4%|▍ | 157/3818 [01:03<25:33, 2.39it/s] 4%|▍ | 158/3818 [01:04<25:29, 2.39it/s] 4%|▍ | 159/3818 [01:04<25:24, 2.40it/s] 4%|▍ | 160/3818 [01:04<25:22, 2.40it/s] 4%|▍ | 161/3818 [01:05<25:20, 2.40it/s] 4%|▍ | 162/3818 [01:05<25:23, 2.40it/s] 4%|▍ | 163/3818 [01:06<25:19, 2.41it/s] 4%|▍ | 164/3818 [01:06<25:23, 2.40it/s] 4%|▍ | 165/3818 [01:07<25:20, 2.40it/s] 4%|▍ | 166/3818 [01:07<25:21, 2.40it/s] 4%|▍ | 167/3818 [01:07<25:23, 2.40it/s] 4%|▍ | 168/3818 [01:08<25:21, 2.40it/s] 4%|▍ | 169/3818 [01:08<25:24, 2.39it/s] 4%|▍ | 170/3818 [01:09<25:22, 2.40it/s] 4%|▍ | 171/3818 [01:09<25:19, 2.40it/s] 5%|▍ | 172/3818 [01:09<25:18, 2.40it/s] 5%|▍ | 173/3818 [01:10<25:16, 2.40it/s] 5%|▍ | 174/3818 [01:10<25:19, 2.40it/s] 5%|▍ | 175/3818 [01:11<25:21, 2.39it/s] 5%|▍ | 176/3818 [01:11<25:16, 2.40it/s] 5%|▍ | 177/3818 [01:12<25:21, 2.39it/s] 5%|▍ | 178/3818 [01:12<25:23, 2.39it/s] 5%|▍ | 179/3818 [01:12<25:22, 2.39it/s] 5%|▍ | 180/3818 [01:13<25:22, 2.39it/s] 5%|▍ | 181/3818 [01:13<25:19, 2.39it/s] 5%|▍ | 182/3818 [01:14<25:21, 2.39it/s] 5%|▍ | 183/3818 [01:14<25:21, 2.39it/s] 5%|▍ | 184/3818 [01:15<25:21, 2.39it/s] 5%|▍ | 185/3818 [01:15<25:25, 2.38it/s] 5%|▍ | 186/3818 [01:15<25:23, 2.38it/s] 5%|▍ | 187/3818 [01:16<25:26, 2.38it/s] 5%|▍ | 188/3818 [01:16<25:25, 2.38it/s] 5%|▍ | 189/3818 [01:17<25:25, 2.38it/s] 5%|▍ | 190/3818 [01:17<25:26, 2.38it/s] 5%|▌ | 191/3818 [01:17<25:22, 2.38it/s] 5%|▌ | 192/3818 [01:18<25:25, 2.38it/s] 5%|▌ | 193/3818 [01:18<25:27, 2.37it/s] 5%|▌ | 194/3818 [01:19<25:26, 2.37it/s] 5%|▌ | 195/3818 [01:19<25:29, 2.37it/s] 5%|▌ | 196/3818 [01:20<25:27, 2.37it/s] 5%|▌ | 197/3818 [01:20<25:26, 2.37it/s] 5%|▌ | 198/3818 [01:20<25:24, 2.37it/s] 5%|▌ | 199/3818 [01:21<25:26, 2.37it/s] 5%|▌ | 200/3818 [01:21<25:28, 2.37it/s] 5%|▌ | 201/3818 [01:22<25:31, 2.36it/s] 5%|▌ | 202/3818 [01:22<25:30, 2.36it/s] 5%|▌ | 203/3818 [01:23<25:30, 2.36it/s] 5%|▌ | 204/3818 [01:23<25:31, 2.36it/s] 5%|▌ | 205/3818 [01:23<25:31, 2.36it/s] 5%|▌ | 206/3818 [01:24<25:28, 2.36it/s] 5%|▌ | 207/3818 [01:24<25:30, 2.36it/s] 5%|▌ | 208/3818 [01:25<25:28, 2.36it/s] 5%|▌ | 209/3818 [01:25<25:29, 2.36it/s] 6%|▌ | 210/3818 [01:25<25:28, 2.36it/s] 6%|▌ | 211/3818 [01:26<25:29, 2.36it/s] 6%|▌ | 212/3818 [01:26<25:29, 2.36it/s] 6%|▌ | 213/3818 [01:27<25:29, 2.36it/s] 6%|▌ | 214/3818 [01:27<25:26, 2.36it/s] 6%|▌ | 215/3818 [01:28<25:26, 2.36it/s] 6%|▌ | 216/3818 [01:28<25:25, 2.36it/s] 6%|▌ | 217/3818 [01:28<25:26, 2.36it/s] 6%|▌ | 218/3818 [01:29<25:24, 2.36it/s] 6%|▌ | 219/3818 [01:29<25:23, 2.36it/s] 6%|▌ | 220/3818 [01:30<25:24, 2.36it/s] 6%|▌ | 221/3818 [01:30<25:25, 2.36it/s] 6%|▌ | 222/3818 [01:31<25:27, 2.35it/s] 6%|▌ | 223/3818 [01:31<25:23, 2.36it/s] 6%|▌ | 224/3818 [01:31<25:26, 2.35it/s] 6%|▌ | 225/3818 [01:32<25:24, 2.36it/s] 6%|▌ | 226/3818 [01:32<25:21, 2.36it/s] 6%|▌ | 227/3818 [01:33<25:24, 2.36it/s] 6%|▌ | 228/3818 [01:33<25:21, 2.36it/s] 6%|▌ | 229/3818 [01:34<25:24, 2.35it/s] 6%|▌ | 230/3818 [01:34<25:22, 2.36it/s] 6%|▌ | 231/3818 [01:34<25:24, 2.35it/s] 6%|▌ | 232/3818 [01:35<25:22, 2.36it/s] 6%|▌ | 233/3818 [01:35<25:21, 2.36it/s] 6%|▌ | 234/3818 [01:36<25:25, 2.35it/s] 6%|▌ | 235/3818 [01:36<25:24, 2.35it/s] 6%|▌ | 236/3818 [01:37<25:27, 2.34it/s] 6%|▌ | 237/3818 [01:37<25:28, 2.34it/s] 6%|▌ | 238/3818 [01:37<25:26, 2.35it/s] 6%|▋ | 239/3818 [01:38<25:29, 2.34it/s] 6%|▋ | 240/3818 [01:38<25:26, 2.34it/s] 6%|▋ | 241/3818 [01:39<25:29, 2.34it/s] 6%|▋ | 242/3818 [01:39<25:28, 2.34it/s] 6%|▋ | 243/3818 [01:40<25:26, 2.34it/s] 6%|▋ | 244/3818 [01:40<25:26, 2.34it/s] 6%|▋ | 245/3818 [01:40<25:26, 2.34it/s] 6%|▋ | 246/3818 [01:41<25:27, 2.34it/s] 6%|▋ | 247/3818 [01:41<25:29, 2.34it/s] 6%|▋ | 248/3818 [01:42<25:29, 2.33it/s] 7%|▋ | 249/3818 [01:42<25:32, 2.33it/s] 7%|▋ | 250/3818 [01:43<25:32, 2.33it/s] 7%|▋ | 251/3818 [01:43<25:33, 2.33it/s] 7%|▋ | 252/3818 [01:43<25:36, 2.32it/s] 7%|▋ | 253/3818 [01:44<25:34, 2.32it/s] 7%|▋ | 254/3818 [01:44<25:33, 2.32it/s] 7%|▋ | 255/3818 [01:45<25:31, 2.33it/s] 7%|▋ | 256/3818 [01:45<25:30, 2.33it/s] 7%|▋ | 257/3818 [01:46<25:32, 2.32it/s] 7%|▋ | 258/3818 [01:46<25:33, 2.32it/s] 7%|▋ | 259/3818 [01:46<25:34, 2.32it/s] 7%|▋ | 260/3818 [01:47<25:33, 2.32it/s] 7%|▋ | 261/3818 [01:47<25:31, 2.32it/s] 7%|▋ | 262/3818 [01:48<25:30, 2.32it/s] 7%|▋ | 263/3818 [01:48<25:32, 2.32it/s] 7%|▋ | 264/3818 [01:49<25:31, 2.32it/s] 7%|▋ | 265/3818 [01:49<25:34, 2.32it/s] 7%|▋ | 266/3818 [01:49<25:32, 2.32it/s] 7%|▋ | 267/3818 [01:50<25:31, 2.32it/s] 7%|▋ | 268/3818 [01:50<25:35, 2.31it/s] 7%|▋ | 269/3818 [01:51<25:30, 2.32it/s] 7%|▋ | 270/3818 [01:51<25:33, 2.31it/s] 7%|▋ | 271/3818 [01:52<25:33, 2.31it/s] 7%|▋ | 272/3818 [01:52<25:33, 2.31it/s] 7%|▋ | 273/3818 [01:52<25:33, 2.31it/s] 7%|▋ | 274/3818 [01:53<25:31, 2.31it/s] 7%|▋ | 275/3818 [01:53<25:35, 2.31it/s] 7%|▋ | 276/3818 [01:54<25:33, 2.31it/s] 7%|▋ | 277/3818 [01:54<25:34, 2.31it/s] 7%|▋ | 278/3818 [01:55<25:33, 2.31it/s] 7%|▋ | 279/3818 [01:55<25:30, 2.31it/s] 7%|▋ | 280/3818 [01:55<25:31, 2.31it/s] 7%|▋ | 281/3818 [01:56<25:28, 2.31it/s] 7%|▋ | 282/3818 [01:56<25:33, 2.31it/s] 7%|▋ | 283/3818 [01:57<25:31, 2.31it/s] 7%|▋ | 284/3818 [01:57<25:33, 2.30it/s] 7%|▋ | 285/3818 [01:58<25:31, 2.31it/s] 7%|▋ | 286/3818 [01:58<25:30, 2.31it/s] 8%|▊ | 287/3818 [01:59<25:32, 2.30it/s] 8%|▊ | 288/3818 [01:59<25:32, 2.30it/s] 8%|▊ | 289/3818 [01:59<25:31, 2.30it/s] 8%|▊ | 290/3818 [02:00<25:29, 2.31it/s] 8%|▊ | 291/3818 [02:00<25:30, 2.31it/s] 8%|▊ | 292/3818 [02:01<25:28, 2.31it/s] 8%|▊ | 293/3818 [02:01<25:26, 2.31it/s] 8%|▊ | 294/3818 [02:02<25:26, 2.31it/s] 8%|▊ | 295/3818 [02:02<25:24, 2.31it/s] 8%|▊ | 296/3818 [02:02<25:28, 2.30it/s] 8%|▊ | 297/3818 [02:03<25:28, 2.30it/s] 8%|▊ | 298/3818 [02:03<25:26, 2.31it/s] 8%|▊ | 299/3818 [02:04<25:24, 2.31it/s] 8%|▊ | 300/3818 [02:04<25:28, 2.30it/s] 8%|▊ | 301/3818 [02:05<25:29, 2.30it/s] 8%|▊ | 302/3818 [02:05<25:29, 2.30it/s] 8%|▊ | 303/3818 [02:05<25:30, 2.30it/s] 8%|▊ | 304/3818 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