pjbhaumik/km3
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-12-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-ms-marco-MiniLM-L-12-v2
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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-ms-marco-MiniLM-L-12-v2
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This model is a fine-tuned version of [cross-encoder/ms-marco-MiniLM-L-12-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-12-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0519
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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: 100
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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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| 84.3752 | 1.0 | 20 | 95.6720 |
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| 34.7287 | 2.0 | 40 | 37.5520 |
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| 17.736 | 3.0 | 60 | 13.6402 |
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| 4.518 | 4.0 | 80 | 3.1808 |
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| 1.2747 | 5.0 | 100 | 1.0527 |
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| 0.3802 | 6.0 | 120 | 0.2666 |
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| 0.1429 | 7.0 | 140 | 0.0969 |
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| 0.0894 | 8.0 | 160 | 0.0368 |
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| 0.0534 | 9.0 | 180 | 0.0403 |
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| 0.0382 | 10.0 | 200 | 0.0497 |
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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 2.17.1
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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-12-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": 12,
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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 sha256:62c23e15ae182678bcd2ec6fe6d91003783e88877608f7f967f9537a74f07c5e
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size 133464836
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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 sha256:9ea036e2bcd95935105f5475a58feba376da1d371bf5bc06b19ee13cc53b2c8d
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size 4219
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vocab.txt
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