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--- |
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base_model: dccuchile/bert-base-spanish-wwm-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- recall |
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model-index: |
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- name: bert-base-spanish-wwm-cased_K5 |
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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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# bert-base-spanish-wwm-cased_K5 |
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This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0182 |
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- F1 Macro: 0.9973 |
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- F1: 0.9980 |
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- F1 Neg: 0.9966 |
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- Acc: 0.9975 |
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- Prec: 0.9980 |
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- Recall: 0.9980 |
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- Mcc: 0.9946 |
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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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- distributed_type: multi-GPU |
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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: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:| |
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| No log | 1.0 | 400 | 0.0263 | 0.9960 | 0.9970 | 0.9949 | 0.9962 | 0.9980 | 0.9961 | 0.9919 | |
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| 0.0591 | 2.0 | 800 | 0.0182 | 0.9973 | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 | |
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| 0.0123 | 3.0 | 1200 | 0.0225 | 0.9973 | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 | |
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| 0.0078 | 4.0 | 1600 | 0.0227 | 0.9973 | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 | |
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| 0.002 | 5.0 | 2000 | 0.0229 | 0.9973 | 0.9980 | 0.9966 | 0.9975 | 0.9980 | 0.9980 | 0.9946 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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