Upload 7 files
Browse files- CECorrelationEvaluator_sts-dev_results.csv +11 -0
- config.json +31 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +16 -0
- vocab.txt +0 -0
CECorrelationEvaluator_sts-dev_results.csv
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epoch,steps,Pearson_Correlation,Spearman_Correlation
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0,-1,0.8629844696887493,0.8596527294018822
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1,-1,0.8625163349469747,0.8591422244456008
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2,-1,0.8626435822387511,0.85956451660678
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3,-1,0.8644876431246158,0.8606351675638202
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4,-1,0.8646001979163409,0.8606108281939284
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5,-1,0.8653602626547123,0.8612569419468663
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6,-1,0.8628049245075982,0.8599911391590234
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7,-1,0.8636204386047313,0.8595385609260403
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8,-1,0.8627988642924628,0.8588752606669621
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9,-1,0.8622224559947367,0.857483526061374
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config.json
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{
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"_name_or_path": "klue-cross-encoder-v1",
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"architectures": [
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"BertForSequenceClassification"
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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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"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": "LABEL_0"
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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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"LABEL_0": 0
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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": "4.21.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 32000
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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 sha256:3f2767964c6b79394e1901988820b5cd978536ed781debdc6d9f492db5c3d42f
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size 442543469
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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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tokenizer_config.json
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{
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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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": "klue-cross-encoder-v1",
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"never_split": null,
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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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