Training complete with metrics
Browse files- README.md +88 -7
- config.json +49 -0
- model.safetensors +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +58 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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-
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## Model description
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This is a BETO base cased model fine-tuned on the CONLL2002 dataset for Named Entity Recognition (NER).
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---
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license: cc-by-4.0
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base_model: NazaGara/NER-fine-tuned-BETO
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tags:
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- generated_from_trainer
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datasets:
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- conll2002
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: beto-base-cased-finetuned-conll2002
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: conll2002
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type: conll2002
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config: es
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split: validation
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args: es
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metrics:
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- name: Precision
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type: precision
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value: 0.8597014925373134
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- name: Recall
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type: recall
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value: 0.8602941176470589
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- name: F1
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type: f1
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value: 0.8599977029975882
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- name: Accuracy
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type: accuracy
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value: 0.978761597037205
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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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# beto-base-cased-finetuned-conll2002
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This model is a fine-tuned version of [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on the conll2002 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1259
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- Precision: 0.8597
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- Recall: 0.8603
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- F1: 0.8600
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- Accuracy: 0.9788
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0154 | 1.0 | 1041 | 0.1064 | 0.8523 | 0.8603 | 0.8563 | 0.9782 |
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| 0.0162 | 2.0 | 2082 | 0.1060 | 0.8556 | 0.8635 | 0.8596 | 0.9790 |
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| 0.0161 | 3.0 | 3123 | 0.1259 | 0.8597 | 0.8603 | 0.8600 | 0.9788 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "NazaGara/NER-fine-tuned-BETO",
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"architectures": [
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"BertForTokenClassification"
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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": "O",
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"1": "B-PER",
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"2": "I-PER",
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"3": "B-ORG",
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"4": "I-ORG",
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"5": "B-LOC",
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"6": "I-LOC",
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"7": "B-MISC",
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"8": "I-MISC"
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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-LOC": 5,
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"B-MISC": 7,
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"B-ORG": 3,
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"B-PER": 1,
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"I-LOC": 6,
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"I-MISC": 8,
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"I-ORG": 4,
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"I-PER": 2,
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"O": 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_past": true,
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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": "4.41.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 31002
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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 sha256:23ed81a0157bbb495dc87cac5b52d752ee24b159d7b4daba761b134e10b11654
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size 437092180
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special_tokens_map.json
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{
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"cls_token": {
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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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},
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"mask_token": {
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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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},
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"pad_token": {
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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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},
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"sep_token": {
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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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},
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"unk_token": {
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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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}
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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": "[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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"1": {
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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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"3": {
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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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"4": {
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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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"5": {
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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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},
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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": false,
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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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"num_labels": 9,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": false,
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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 sha256:977708e479982844c3f459673a008958d5989dcaf7d869758e87c14da5904627
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size 5112
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vocab.txt
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