Training in progress epoch 0
Browse files- config.json +60 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- vocab.txt +0 -0
config.json
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"BertForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "B-corporation",
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"1": "B-creative_work",
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"2": "B-event",
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"3": "B-group",
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"4": "B-location",
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"5": "B-person",
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"6": "B-product",
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"7": "I-corporation",
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"8": "I-creative_work",
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"9": "I-event",
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"10": "I-group",
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"11": "I-location",
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"12": "I-person",
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"13": "I-product",
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"14": "O"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-corporation": 0,
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"B-creative_work": 1,
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"B-event": 2,
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"B-group": 3,
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"B-location": 4,
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"B-person": 5,
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"B-product": 6,
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"I-corporation": 7,
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"I-creative_work": 8,
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"I-event": 9,
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"I-group": 10,
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"I-location": 11,
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"I-person": 12,
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"I-product": 13,
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"O": 14
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.20.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a54b19d7e8098ac83c78417320f5966cf77b4e9a6f3b7b59c0fc7a4227fddf0
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size 430992433
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer.json
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The diff for this file is too large to render.
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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "bert-base-cased",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"special_tokens_map_file": null,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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The diff for this file is too large to render.
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