Add model

added_tokens.json

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+{"<e1>": 30000, "</e1>": 30001, "<e2>": 30002, "</e2>": 30003}

config.json

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+{
+  "_name_or_path": "albert-large-v2",
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "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,
+  "inner_group_num": 1,
+  "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": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 16,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 24,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.2",
+  "type_vocab_size": 2,
+  "vocab_size": 30004
+}

eval_results.txt

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+cls_report =               precision    recall  f1-score   support
+
+         0.0     0.8916    0.7957    0.8409        93
+         1.0     0.8537    0.8537    0.8537        82
+         2.0     0.6962    0.6875    0.6918        80
+         3.0     1.0000    1.0000    1.0000        57
+         4.0     0.7714    0.8308    0.8000        65
+         5.0     0.9494    0.9740    0.9615        77
+         6.0     0.9889    1.0000    0.9944        89
+         7.0     0.9474    0.9863    0.9664        73
+         8.0     1.0000    1.0000    1.0000        13
+         9.0     1.0000    1.0000    1.0000         9
+
+    accuracy                         0.8903       638
+   macro avg     0.9098    0.9128    0.9109       638
+weighted avg     0.8903    0.8903    0.8897       638
+
+eval_loss = 0.29622152000665664
+macro_f1 = 0.9108786349245351
+macro_p = 0.9098480303268863
+macro_r = 0.9127954035974767
+mcc = 0.8756280066894239

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": "albert-large-v2", "model_type": "albert", "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": "albert-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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+size 133257527

pytorch_model.bin

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scheduler.pt

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special_tokens_map.json

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spiece.model

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test_eval.txt

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+Default classification report:
+               precision    recall  f1-score   support
+
+        equal     0.6316    0.8000    0.7059        15
+      greater     0.8889    0.7273    0.8000        11
+greater-equal     0.6333    0.9048    0.7451        21
+         less     1.0000    0.5000    0.6667         2
+   less-equal     0.7222    0.9286    0.8125        14
+    necessity     0.8654    0.8738    0.8696       206
+         none     0.7616    0.6550    0.7043       200
+  not-part-of     1.0000    0.5000    0.6667         2
+      part-of     0.7135    0.8148    0.7608       162
+    selection     0.8430    0.8069    0.8246       233
+
+     accuracy                         0.7910       866
+    macro avg     0.8060    0.7511    0.7556       866
+ weighted avg     0.7959    0.7910    0.7903       866
+
+mcc = 0.7350731543361181
+precision(macro) = 0.8059598755041998
+recall(macro) = 0.7511074235977566
+f1_score(macro) = 0.7556048338085604

tokenizer_config.json

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training_args.bin

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