Training in progress, step 500
Browse files- .gitignore +1 -0
- config.json +24 -0
- pytorch_model.bin +3 -0
- runs/Jun07_11-23-51_botika/1654575848.8329837/events.out.tfevents.1654575848.botika.18140.1 +3 -0
- runs/Jun07_11-23-51_botika/events.out.tfevents.1654575848.botika.18140.0 +3 -0
- runs/Jun07_11-26-04_botika/1654575976.2936635/events.out.tfevents.1654575976.botika.18438.1 +3 -0
- runs/Jun07_11-26-04_botika/events.out.tfevents.1654575976.botika.18438.0 +3 -0
- runs/Jun07_11-28-25_botika/1654576137.3212664/events.out.tfevents.1654576137.botika.18561.1 +3 -0
- runs/Jun07_11-28-25_botika/events.out.tfevents.1654576137.botika.18561.0 +3 -0
- runs/Jun07_11-29-40_botika/1654576196.1059592/events.out.tfevents.1654576196.botika.18710.1 +3 -0
- runs/Jun07_11-29-40_botika/events.out.tfevents.1654576196.botika.18710.0 +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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"DistilBertForQuestionAnswering"
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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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"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": "4.19.2",
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"vocab_size": 30522
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}
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pytorch_model.bin
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runs/Jun07_11-23-51_botika/1654575848.8329837/events.out.tfevents.1654575848.botika.18140.1
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runs/Jun07_11-28-25_botika/1654576137.3212664/events.out.tfevents.1654576137.botika.18561.1
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runs/Jun07_11-29-40_botika/1654576196.1059592/events.out.tfevents.1654576196.botika.18710.1
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runs/Jun07_11-29-40_botika/events.out.tfevents.1654576196.botika.18710.0
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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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