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added_tokens.json

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+{"<e>": 250002, "</e>": 250003}

config.json

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+{
+  "_name_or_path": "xlm-roberta-large",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250004
+}

eval_results.txt

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+accuracy = 0.8186874304783093
+cls_report =               precision    recall  f1-score   support
+
+         0.0     0.8040    0.8608    0.8314       467
+         1.0     0.8371    0.7731    0.8039       432
+
+    accuracy                         0.8187       899
+   macro avg     0.8205    0.8170    0.8176       899
+weighted avg     0.8199    0.8187    0.8182       899
+
+eval_loss = 0.41150999863942467
+fn = 98
+fp = 65
+macro_f1 = 0.8176441087786235
+mcc = 0.6375173221080976
+tn = 402
+tp = 334
+weighted_f1 = 0.8181811125946382
+weighted_p = 0.8205463659147869
+weighted_r = 0.8169809263224681

model_args.json

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+{"adam_epsilon": 1e-08, "begin_tag": "<e>", "best_model_dir": "best_model", "cache_dir": "temp/cache_dir/", "config": {}, "custom_layer_parameters": [], "custom_parameter_groups": [], "dataloader_num_workers": 70, "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, "end_tag": "</e>", "eval_batch_size": 64, "evaluate_during_training": true, "evaluate_during_training_silent": false, "evaluate_during_training_steps": 100, "evaluate_during_training_verbose": true, "evaluate_each_epoch": true, "fp16": false, "gradient_accumulation_steps": 1, "learning_rate": 1e-05, "local_rank": -1, "logging_steps": 100, "manual_seed": 777, "max_grad_norm": 1.0, "max_seq_length": 120, "model_name": "xlm-roberta-large", "model_type": "xlmroberta", "multiprocessing_chunksize": 500, "n_gpu": 1, "no_cache": false, "no_save": false, "num_train_epochs": 3, "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_steps": 100, "save_recent_only": true, "silent": false, "tensorboard_dir": null, "thread_count": null, "train_batch_size": 8, "train_custom_parameters_only": false, "use_cached_eval_features": false, "use_early_stopping": true, "use_multiprocessing": false, "wandb_kwargs": {"group": "en-en_xlm-roberta-large_P_concat", "job_type": "2"}, "wandb_project": "TransWiC-groups", "warmup_ratio": 0.1, "warmup_steps": 304, "weight_decay": 0, "skip_special_tokens": true, "model_class": "ClassificationModel", "labels_list": [0, 1], "labels_map": {}, "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, "tagging": true, "strategy": "P", "special_tags": ["<e>", "</e>"], "merge_n": 2, "merge_type": "concat"}

optimizer.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3ee7a036085644de3c5bbcb02f03c1a7faf182181778945b5fdbc0d1146b433e
+size 4504578173

pytorch_model.bin

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+size 2256539517

scheduler.pt

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+size 627

sentencepiece.bpe.model

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+size 5069051

special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}}

test_eval.txt

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+Default classification report:
+              precision    recall  f1-score   support
+
+           F     0.8996    0.8960    0.8978       500
+           T     0.8964    0.9000    0.8982       500
+
+    accuracy                         0.8980      1000
+   macro avg     0.8980    0.8980    0.8980      1000
+weighted avg     0.8980    0.8980    0.8980      1000
+
+
+ADJ
+Accuracy = 0.9097222222222222
+Weighted Recall = 0.9097222222222222
+Weighted Precision = 0.9097316448062718
+Weighted F1 = 0.909682885499879
+Macro Recall = 0.9090557275541795
+Macro Precision = 0.9097693351424694
+Macro F1 = 0.9093681917211328
+ADV
+Accuracy = 0.7333333333333333
+Weighted Recall = 0.7333333333333333
+Weighted Precision = 0.7446428571428572
+Weighted F1 = 0.7357466063348416
+Macro Recall = 0.7361111111111112
+Macro Precision = 0.7276785714285714
+Macro F1 = 0.7285067873303168
+NOUN
+Accuracy = 0.8958333333333334
+Weighted Recall = 0.8958333333333334
+Weighted Precision = 0.8958405073461891
+Weighted F1 = 0.8958337069811766
+Macro Recall = 0.8958390128416673
+Macro Precision = 0.8958333333333333
+Macro F1 = 0.8958329596854901
+VERB
+Accuracy = 0.912751677852349
+Weighted Recall = 0.912751677852349
+Weighted Precision = 0.9128260575753482
+Weighted F1 = 0.9127477477477476
+Macro Recall = 0.912751677852349
+Macro Precision = 0.912826057575348
+Macro F1 = 0.9127477477477477

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "sp_model_kwargs": {}, "model_max_length": 512, "do_lower_case": false, "special_tokens_map_file": null, "tokenizer_file": "/data2/hh2/hf_cache/transformers/7766c86e10505ed9b39af34e456480399bf06e35b36b8f2b917460a2dbe94e59.a984cf52fc87644bd4a2165f1e07e0ac880272c1e82d648b4674907056912bd7", "name_or_path": "xlm-roberta-large", "tokenizer_class": "XLMRobertaTokenizer"}

training_args.bin

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