Add model

added_tokens.json

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+{"<e1>": 28996, "</e1>": 28997, "<e2>": 28998, "</e2>": 28999}

config.json

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+{
+  "_name_or_path": "bert-large-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 29000
+}

eval_results.txt

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+cls_report =               precision    recall  f1-score   support
+
+         0.0     0.9595    0.7634    0.8503        93
+         1.0     0.8021    0.9390    0.8652        82
+         2.0     0.7534    0.6875    0.7190        80
+         3.0     1.0000    1.0000    1.0000        57
+         4.0     0.8116    0.8615    0.8358        65
+         5.0     0.9620    0.9870    0.9744        77
+         6.0     0.9780    1.0000    0.9889        89
+         7.0     0.9481    1.0000    0.9733        73
+         8.0     1.0000    1.0000    1.0000        13
+         9.0     1.0000    1.0000    1.0000         9
+
+    accuracy                         0.9028       638
+   macro avg     0.9215    0.9239    0.9207       638
+weighted avg     0.9049    0.9028    0.9012       638
+
+eval_loss = 0.2609917640686035
+macro_f1 = 0.9206824280993045
+macro_p = 0.9214660895755212
+macro_r = 0.9238516699010404
+mcc = 0.8905145977958459

model_args.json

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+{"adam_epsilon": 1e-08, "best_model_dir": "outputs/best_model", "cache_dir": "temp/cache_dir", "config": {}, "custom_layer_parameters": [], "custom_parameter_groups": [], "dataloader_num_workers": 1, "do_lower_case": false, "dynamic_quantize": false, "early_stopping_consider_epochs": false, "early_stopping_delta": 0, "early_stopping_metric": "eval_loss", "early_stopping_metric_minimize": true, "early_stopping_patience": 10, "encoding": null, "eval_batch_size": 64, "evaluate_during_training": true, "evaluate_during_training_silent": false, "evaluate_during_training_steps": 16, "evaluate_during_training_verbose": true, "evaluate_each_epoch": true, "fp16": false, "gradient_accumulation_steps": 1, "learning_rate": 1e-05, "local_rank": -1, "logging_steps": 16, "manual_seed": 157, "max_grad_norm": 1.0, "max_seq_length": 128, "model_name": "bert-large-cased", "model_type": "bert", "multiprocessing_chunksize": 500, "n_gpu": 1, "no_cache": false, "no_save": false, "not_saved_args": [], "num_train_epochs": 5, "output_dir": "temp/outputs", "overwrite_output_dir": true, "process_count": 70, "quantized_model": false, "reprocess_input_data": true, "save_best_model": true, "save_eval_checkpoints": false, "save_model_every_epoch": false, "save_optimizer_and_scheduler": true, "save_recent_only": true, "save_steps": 16, "silent": false, "tensorboard_dir": null, "thread_count": null, "train_batch_size": 16, "train_custom_parameters_only": false, "use_cached_eval_features": false, "use_early_stopping": true, "use_multiprocessing": true, "wandb_kwargs": {"name": "bert-large_1e-05_5_strain"}, "wandb_project": "relation-extraction", "warmup_ratio": 0.1, "warmup_steps": 180, "weight_decay": 0, "skip_special_tokens": true, "model_class": "REModel", "labels_list": ["selection", "necessity", "none", "greater", "part-of", "equal", "greater-equal", "less-equal", "not-part-of", "less"], "labels_map": {"selection": 0, "necessity": 1, "none": 2, "greater": 3, "part-of": 4, "equal": 5, "greater-equal": 6, "less-equal": 7, "not-part-of": 8, "less": 9}, "lazy_delimiter": "\t", "lazy_labels_column": 1, "lazy_loading": false, "lazy_loading_start_line": 1, "lazy_text_a_column": null, "lazy_text_b_column": null, "lazy_text_column": 0, "onnx": false, "regression": false, "sliding_window": false, "stride": 0.8, "tie_value": 1, "special_tags": ["<e1>", "<e2>"]}

optimizer.pt

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+oid sha256:efdad27900c657f635bdd7febbae61989f747e194540d2d1115e28158a39eaf7
+size 2660663621

pytorch_model.bin

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+oid sha256:f1b1787704f0281030483854d40332760441d392fd00a54024a89d6075c2c5dc
+size 1334579957

scheduler.pt

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+oid sha256:78c7876c3cf33ba6355acd8a4e1610138c157a71efc5ca0f1edba461142b9a9e
+size 627

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

test_eval.txt

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+Default classification report:
+               precision    recall  f1-score   support
+
+        equal     0.7647    0.8667    0.8125        15
+      greater     1.0000    0.9091    0.9524        11
+greater-equal     0.6207    0.8571    0.7200        21
+         less     1.0000    0.5000    0.6667         2
+   less-equal     0.7647    0.9286    0.8387        14
+    necessity     0.8062    0.8883    0.8453       206
+         none     0.7834    0.6150    0.6891       200
+  not-part-of     1.0000    1.0000    1.0000         2
+      part-of     0.7143    0.8025    0.7558       162
+    selection     0.8259    0.7940    0.8096       233
+
+     accuracy                         0.7829       866
+    macro avg     0.8280    0.8161    0.8090       866
+ weighted avg     0.7865    0.7829    0.7805       866
+
+mcc = 0.7252961407864995
+precision(macro) = 0.8279886882633785
+recall(macro) = 0.8161281928146451
+f1_score(macro) = 0.8090040477874731

tokenizer_config.json

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training_args.bin

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training_progress_scores.csv

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