End of training
Browse files- README.md +81 -0
- config.json +105 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- runs/Dec20_04-48-57_8f07b2673358/events.out.tfevents.1703047752.8f07b2673358.237.0 +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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---
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language:
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- en
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license: mit
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base_model: roberta-base
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tags:
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- pytorch
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- RobertaForTokenClassification
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- named-entity-recognition
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- roberta-base
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- generated_from_trainer
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metrics:
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- recall
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- precision
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- f1
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- accuracy
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model-index:
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- name: roberta-base-ontonotes
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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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# roberta-base-ontonotes
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the tner/ontonotes5 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0695
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- Recall: 0.9227
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- Precision: 0.9013
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- F1: 0.9118
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- Accuracy: 0.9820
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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: 8e-05
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- train_batch_size: 32
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- eval_batch_size: 160
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- seed: 75241309
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- training_steps: 6000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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| 0.1305 | 0.31 | 600 | 0.1169 | 0.8550 | 0.8139 | 0.8340 | 0.9681 |
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| 0.118 | 0.63 | 1200 | 0.0925 | 0.8769 | 0.8592 | 0.8680 | 0.9750 |
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| 0.0937 | 0.94 | 1800 | 0.0874 | 0.8939 | 0.8609 | 0.8771 | 0.9764 |
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| 0.0698 | 1.25 | 2400 | 0.0821 | 0.9066 | 0.8775 | 0.8918 | 0.9784 |
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| 0.0663 | 1.56 | 3000 | 0.0827 | 0.9124 | 0.8764 | 0.8940 | 0.9789 |
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| 0.0624 | 1.88 | 3600 | 0.0732 | 0.9179 | 0.8868 | 0.9021 | 0.9804 |
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| 0.0364 | 2.19 | 4200 | 0.0750 | 0.9204 | 0.8968 | 0.9085 | 0.9816 |
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| 0.0429 | 2.5 | 4800 | 0.0699 | 0.9198 | 0.9031 | 0.9114 | 0.9818 |
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| 0.0323 | 2.82 | 5400 | 0.0697 | 0.9227 | 0.9008 | 0.9116 | 0.9819 |
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| 0.0334 | 3.13 | 6000 | 0.0695 | 0.9227 | 0.9013 | 0.9118 | 0.9820 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "roberta-base",
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"architectures": [
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"RobertaForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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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": "O",
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"1": "B-CARDINAL",
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"2": "B-DATE",
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"3": "I-DATE",
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"4": "B-PERSON",
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"5": "I-PERSON",
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"6": "B-NORP",
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"7": "B-GPE",
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"8": "I-GPE",
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"9": "B-LAW",
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"10": "I-LAW",
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"11": "B-ORG",
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"12": "I-ORG",
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"13": "B-PERCENT",
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"14": "I-PERCENT",
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"15": "B-ORDINAL",
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"16": "B-MONEY",
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"17": "I-MONEY",
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"18": "B-WORK_OF_ART",
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"19": "I-WORK_OF_ART",
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"20": "B-FAC",
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"21": "B-TIME",
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"22": "I-CARDINAL",
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"23": "B-LOC",
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"24": "B-QUANTITY",
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"25": "I-QUANTITY",
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"26": "I-NORP",
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"27": "I-LOC",
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"28": "B-PRODUCT",
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"29": "I-TIME",
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"30": "B-EVENT",
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"31": "I-EVENT",
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"32": "I-FAC",
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"33": "B-LANGUAGE",
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"34": "I-PRODUCT",
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"35": "I-ORDINAL",
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"36": "I-LANGUAGE"
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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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"B-CARDINAL": 1,
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"B-DATE": 2,
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"B-EVENT": 30,
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"B-FAC": 20,
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"B-GPE": 7,
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"B-LANGUAGE": 33,
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"B-LAW": 9,
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"B-LOC": 23,
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"B-MONEY": 16,
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"B-NORP": 6,
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"B-ORDINAL": 15,
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"B-ORG": 11,
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"B-PERCENT": 13,
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"B-PERSON": 4,
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"B-PRODUCT": 28,
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"B-QUANTITY": 24,
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"B-TIME": 21,
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"B-WORK_OF_ART": 18,
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"I-CARDINAL": 22,
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"I-DATE": 3,
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"I-EVENT": 31,
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"I-FAC": 32,
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"I-GPE": 8,
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"I-LANGUAGE": 36,
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"I-LAW": 10,
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"I-LOC": 27,
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"I-MONEY": 17,
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"I-NORP": 26,
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"I-ORDINAL": 35,
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"I-ORG": 12,
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"I-PERCENT": 14,
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"I-PERSON": 5,
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"I-PRODUCT": 34,
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"I-QUANTITY": 25,
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"I-TIME": 29,
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"I-WORK_OF_ART": 19,
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"O": 0
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.36.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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merges.txt
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc3d51a09efb4572a028ddf52a1966fa0f87a1e4b93d18c48e81117095e77fe0
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size 496357908
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runs/Dec20_04-48-57_8f07b2673358/events.out.tfevents.1703047752.8f07b2673358.237.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:93e31623e8ab5ac8f466256e96ea64a1b0c21e4dad53a19955d581dd3496d5ff
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size 20406
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<pad>",
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"sep_token": "</s>",
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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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"add_prefix_space": true,
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"added_tokens_decoder": {
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"0": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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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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"1": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": true,
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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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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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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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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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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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"50264": {
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"content": "<mask>",
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"lstrip": true,
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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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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
|
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"cls_token": "<s>",
|
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"eos_token": "</s>",
|
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"errors": "replace",
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"mask_token": "<mask>",
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"model_max_length": 512,
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"tokenizer_class": "RobertaTokenizer",
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"trim_offsets": true,
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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 sha256:2f987dc33457fce4f55e8d6a4c10621153de07726425889ff9502c861b84f582
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size 4728
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vocab.json
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