nreimers commited on
Commit
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1 Parent(s): c1a44ab
CECorrelationEvaluator_sts-dev_results.csv ADDED
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+ epoch,steps,Pearson_Correlation,Spearman_Correlation
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README.md ADDED
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+ # Cross-Encoder for Quora Duplicate Questions Detection
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+ This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
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+
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+ ## Training Data
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+ This model was trained on the [STS benchmark dataset](http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark). The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.
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+
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+
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+ ## Usage and Performance
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+
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+ Pre-trained models can be used like this:
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+ ```
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+ from sentence_transformers import CrossEncoder
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+ model = CrossEncoder('model_name')
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+ scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])
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+ ```
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+
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+ The model will predict scores for the pairs `('Sentence 1', 'Sentence 2')` and `('Sentence 3', 'Sentence 4')`.
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+
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+ You can use this model also without sentence_transformers and by just using Transformers ``AutoModel`` class
config.json ADDED
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+ {
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+ "_name_or_path": "output/TinyBERT_L-4-nli/",
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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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+ "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": 312,
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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": 1200,
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+ "label2id": {
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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": 4,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "type_vocab_size": 2,
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+ "vocab_size": 30522
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+ }
pytorch_model.bin ADDED
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special_tokens_map.json ADDED
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+ {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
tokenizer_config.json ADDED
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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": "/home/ukp-reimers/.cache/huggingface/transformers/f96b11e14fec8f4be06121e7f6bbe07f82216bf7d75ad76fe3a81251e8895d69.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "output/TinyBERT_L-4-nli/", "do_basic_tokenize": true, "never_split": null}
vocab.txt ADDED
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