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--- |
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library_name: transformers |
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base_model: dccuchile/bert-base-spanish-wwm-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- biobert_json |
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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: bert-base-spanish-wwm-uncased-finetuned-ner1 |
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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: biobert_json |
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type: biobert_json |
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config: Biobert_json |
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split: validation |
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args: Biobert_json |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9483257314495495 |
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- name: Recall |
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type: recall |
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value: 0.9656754460492778 |
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- name: F1 |
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type: f1 |
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value: 0.9569219543681419 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9766181574620958 |
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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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# bert-base-spanish-wwm-uncased-finetuned-ner |
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the biobert_json dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1423 |
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- Precision: 0.9483 |
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- Recall: 0.9657 |
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- F1: 0.9569 |
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- Accuracy: 0.9766 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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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| 0.0179 | 1.0 | 612 | 0.1292 | 0.9547 | 0.9629 | 0.9588 | 0.9779 | |
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| 0.0133 | 2.0 | 1224 | 0.1574 | 0.9463 | 0.9684 | 0.9572 | 0.9766 | |
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| 0.0146 | 3.0 | 1836 | 0.1179 | 0.9500 | 0.9622 | 0.9561 | 0.9769 | |
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| 0.0238 | 4.0 | 2448 | 0.1388 | 0.9441 | 0.9677 | 0.9557 | 0.9759 | |
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| 0.0152 | 5.0 | 3060 | 0.1442 | 0.9430 | 0.9634 | 0.9531 | 0.9754 | |
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| 0.0155 | 6.0 | 3672 | 0.1401 | 0.9480 | 0.9641 | 0.9560 | 0.9760 | |
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| 0.0126 | 7.0 | 4284 | 0.1411 | 0.9468 | 0.9676 | 0.9571 | 0.9769 | |
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| 0.0131 | 8.0 | 4896 | 0.1427 | 0.9484 | 0.9657 | 0.9570 | 0.9767 | |
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| 0.0117 | 9.0 | 5508 | 0.1391 | 0.9485 | 0.9651 | 0.9567 | 0.9767 | |
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| 0.0116 | 10.0 | 6120 | 0.1423 | 0.9483 | 0.9657 | 0.9569 | 0.9766 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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