nishantyadav
commited on
Commit
•
6226c92
1
Parent(s):
2ba776b
Upload 8 files
Browse filesAdding model files
- CERerankingEvaluator_train-eval_results.csv +127 -0
- config.json +33 -0
- orig_param_for_run.json +10 -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
CERerankingEvaluator_train-eval_results.csv
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config.json
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{
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"_name_or_path": "bert-base-uncased",
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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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"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": "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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"output_hidden_states": true,
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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": "4.26.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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orig_param_for_run.json
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{
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"base_model_name": "bert-base-uncased",
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"use_embed_ce_model": 1,
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"res_dir": "../../results/9_BEIR_CrossEnc/basemodel=bert_base_ce_pool=embed_loss=bce_from_scratch_seed=0",
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"evaluation_steps": 5000,
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"train_batch_size": 32,
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"lr": 2e-05,
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"disable_wandb": 0,
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"seed": 0
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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:b71a4c8448503649a26c38e7ae273df1d699d6a8504a0a629ae60d0a817502b6
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size 438003053
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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_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"name_or_path": "bert-base-uncased",
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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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