Training in progress, step 500
Browse files- .gitignore +1 -0
- config.json +25 -0
- pytorch_model.bin +3 -0
- runs/May18_17-18-35_RHIT-PW01EG3Z/1684444722.1872745/events.out.tfevents.1684444722.RHIT-PW01EG3Z.5990.1 +3 -0
- runs/May18_17-18-35_RHIT-PW01EG3Z/events.out.tfevents.1684444722.RHIT-PW01EG3Z.5990.0 +3 -0
- runs/May18_17-23-39_RHIT-PW01EG3Z/1684445023.485564/events.out.tfevents.1684445023.RHIT-PW01EG3Z.6393.1 +3 -0
- runs/May18_17-23-39_RHIT-PW01EG3Z/events.out.tfevents.1684445023.RHIT-PW01EG3Z.6393.0 +3 -0
- runs/May18_17-24-06_RHIT-PW01EG3Z/1684445048.8145232/events.out.tfevents.1684445048.RHIT-PW01EG3Z.6532.1 +3 -0
- runs/May18_17-24-06_RHIT-PW01EG3Z/events.out.tfevents.1684445048.RHIT-PW01EG3Z.6532.0 +3 -0
- runs/May18_17-26-17_RHIT-PW01EG3Z/1684445180.1405792/events.out.tfevents.1684445180.RHIT-PW01EG3Z.6914.1 +3 -0
- runs/May18_17-26-17_RHIT-PW01EG3Z/events.out.tfevents.1684445180.RHIT-PW01EG3Z.6914.0 +3 -0
- runs/May18_17-26-51_RHIT-PW01EG3Z/1684445215.5401995/events.out.tfevents.1684445215.RHIT-PW01EG3Z.7032.1 +3 -0
- runs/May18_17-26-51_RHIT-PW01EG3Z/events.out.tfevents.1684445215.RHIT-PW01EG3Z.7032.0 +3 -0
- runs/May18_17-29-40_RHIT-PW01EG3Z/1684445384.0818138/events.out.tfevents.1684445384.RHIT-PW01EG3Z.7262.1 +3 -0
- runs/May18_17-29-40_RHIT-PW01EG3Z/events.out.tfevents.1684445384.RHIT-PW01EG3Z.7262.0 +3 -0
- runs/May18_17-31-25_RHIT-PW01EG3Z/1684445489.590762/events.out.tfevents.1684445489.RHIT-PW01EG3Z.7425.1 +3 -0
- runs/May18_17-31-25_RHIT-PW01EG3Z/events.out.tfevents.1684445489.RHIT-PW01EG3Z.7425.0 +3 -0
- runs/May18_17-33-11_RHIT-PW01EG3Z/1684445595.458117/events.out.tfevents.1684445595.RHIT-PW01EG3Z.7575.1 +3 -0
- runs/May18_17-33-11_RHIT-PW01EG3Z/events.out.tfevents.1684445595.RHIT-PW01EG3Z.7575.0 +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
.gitignore
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checkpoint-*/
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.11.3",
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"vocab_size": 30522
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}
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pytorch_model.bin
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "distilbert-base-uncased", "tokenizer_class": "DistilBertTokenizer"}
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training_args.bin
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vocab.txt
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