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--- |
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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-finetuned-ner-1 |
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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: 0.861199 |
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- name: Recall |
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type: recall |
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value: 0.871094 |
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- name: F1 |
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type: f1 |
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value: 0.866118 |
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- name: Accuracy |
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type: accuracy |
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value: 0.972756 |
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--- |
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# beto-finetuned-ner-1 |
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Este es modelo resultado de un finetuning de |
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[NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) sobre el conll2002 dataset. |
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Los siguientes son los resultados sobre el conjunto de evaluación: |
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- Loss: 0.002421 |
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- Precision: 0.861199 |
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- Recall: 0.871094 |
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- F1: 0.8851 |
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- Accuracy: 0,972756 |
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## Model description |
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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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- weight_decay: 0.001 |
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- num_epochs: 8 |
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### Training results |
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| Epoch | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-----:|:-------------:|:---------------:|:---------:|:-------:|:-------:|:--------:| |
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| 1 | 0.004500 | 0.271499 | 0.854365 | 0.868107| 0.861181| 0.971268 | |
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| 2 | 0.004000 | 0.283811 | 0.839605 | 0.840763| 0.840184| 0.966170 | |
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| 3 | 0.003900 | 0.261076 | 0.849651 | 0.867417| 0.858442| 0.970664 | |
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| 4 | 0.002600 | 0.277270 | 0.858379 | 0.866268| 0.862306| 0.971702 | |
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| 5 | 0.002000 | 0.270548 | 0.859149 | 0.871783| 0.865420| 0.971563 | |
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| 6 | 0.001800 | 0.279797 | 0.857305 | 0.868336| 0.862785| 0.971609 | |
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| 7 | 0.001800 | 0.281091 | 0.857467 | 0.868107| 0.862754| 0.971966 | |
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| 8 | 0.001100 | 0.284128 | 0.861199 | 0.871094| 0.866118| 0.972756 | |
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