pjbhaumik/km-cross-encoder2
Browse files- README.md +67 -0
- config.json +34 -0
- model.safetensors +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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license: apache-2.0
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base_model: cross-encoder/ms-marco-MiniLM-L-6-v2
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tags:
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- generated_from_trainer
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model-index:
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- name: crossencoder-km1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# crossencoder-km1
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This model is a fine-tuned version of [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0889
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 80
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- eval_batch_size: 80
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 99.5928 | 1.0 | 13 | 102.9756 |
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| 98.0949 | 2.0 | 26 | 99.8849 |
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| 95.3147 | 3.0 | 39 | 92.5186 |
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| 76.7659 | 4.0 | 52 | 69.9192 |
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| 54.0033 | 5.0 | 65 | 21.3535 |
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| 20.7192 | 6.0 | 78 | 7.2049 |
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| 3.2855 | 7.0 | 91 | 2.0372 |
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| 0.9629 | 8.0 | 104 | 0.3949 |
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| 0.4633 | 9.0 | 117 | 0.1386 |
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| 0.2156 | 10.0 | 130 | 0.0975 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.0.1
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- Datasets 2.17.0
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "cross-encoder/ms-marco-MiniLM-L-6-v2",
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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": 384,
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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": 1536,
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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": 6,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "regression",
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"sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
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"torch_dtype": "float32",
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"transformers_version": "4.37.2",
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:98d4c651e4369c3d33de5e192606c39264aa45b3e9d9c2d055d3c8d3656b0ab5
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size 90866412
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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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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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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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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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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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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:deafebc61456310c26a138c83b25911d8768755817dc0fc13ca717640fe240f9
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size 4155
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vocab.txt
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