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--- |
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base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-english |
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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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--- |
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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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# xml-roberta-large-finetuned-ner |
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Los siguientes son los resultados sobre el conjunto de evaluación: |
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- 'eval_loss': 0.0929097980260849, |
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- 'eval_precision': 0.8704318936877077, |
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- 'eval_recall': 0.8833942118572633, |
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- 'eval_f1': 0.8768651513038628, |
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- 'eval_accuracy': 0.982701988941157, |
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## Model description |
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Este es el modelo más grande de roberta [FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english)- |
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Este modelo fue ajustado usando el framework Kaggle [https://www.kaggle.com/settings]. Para realizar el preentrenamiento del modelo se tuvo que crear un directorio temporal en Kaggle |
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con el fin de almacenar de manera temoporal el modelo que pesa alrededor de 35 Gz. |
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The following hyperparameters were used during training: |
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- eval_strategy="epoch", |
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- save_strategy="epoch", |
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- learning_rate=2e-5, # (Aprendizaje se esta cambiando) |
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- per_device_train_batch_size=16, |
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- per_device_eval_batch_size=16, |
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- num_train_epochs=5, |
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- weight_decay=0.1, |
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- max_grad_norm=1.0, |
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- adam_epsilon=1e-5, |
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- fp16=True, |
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- save_total_limit=2, |
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- load_best_model_at_end=True, |
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- push_to_hub=True, |
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- metric_for_best_model="f1", |
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- seed=42, |
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| Metric | Value | |
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|-----------------|-------------| |
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| eval_loss | 0.12918254733085632 | |
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| eval_precision | 0.8674463937621832 | |
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| eval_recall | 0.8752458555774094 | |
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| eval_f1 | 0.8713286713286713 | |
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| eval_accuracy | 0.9813980358174466 | |
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| eval_runtime | 3.6357 | |
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| eval_samples_per_second | 417.526 | |
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| eval_steps_per_second | 26.13 | |
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| epoch | 5.0 | |
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| Label | Precision | Recall | F1 | Number | |
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|--------|-----------|--------|------------|--------| |
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| LOC | 0.8867924528301887 | 0.8238007380073801 | 0.8541367766618843 | 1084 | |
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| MISC | 0.7349726775956285 | 0.7911764705882353 | 0.7620396600566574 | 340 | |
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| ORG | 0.8400272294077604 | 0.8814285714285715 | 0.8602300453119553 | 1400 | |
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| PER | 0.9599465954606141 | 0.9782312925170068 | 0.9690026954177898 | 735 | |
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