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--- |
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library_name: transformers |
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base_model: mrm8488/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es |
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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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model-index: |
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- name: fge-robos-qa-model |
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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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# fge-robos-qa-model |
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This model is a fine-tuned version of [mrm8488/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es](https://huggingface.co/mrm8488/bert-base-spanish-wwm-cased-finetuned-spa-squad2-es) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0088 |
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- Model Preparation Time: 0.0077 |
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- Exact: 55.7377 |
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- F1: 82.8805 |
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- Total: 915 |
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- Hasans Exact: 55.7377 |
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- Hasans F1: 82.8805 |
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- Hasans Total: 915 |
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- Best Exact: 55.7377 |
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- Best Exact Thresh: 0.0 |
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- Best F1: 82.8805 |
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- Best F1 Thresh: 0.0 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Exact | F1 | Total | Hasans Exact | Hasans F1 | Hasans Total | Best Exact | Best Exact Thresh | Best F1 | Best F1 Thresh | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:|:-------:|:-----:|:------------:|:---------:|:------------:|:----------:|:-----------------:|:-------:|:--------------:| |
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| No log | 1.0 | 58 | 0.8963 | 0.0077 | 54.2077 | 81.4281 | 915 | 54.2077 | 81.4281 | 915 | 54.2077 | 0.0 | 81.4281 | 0.0 | |
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| No log | 2.0 | 116 | 0.9578 | 0.0077 | 54.9727 | 82.3694 | 915 | 54.9727 | 82.3694 | 915 | 54.9727 | 0.0 | 82.3694 | 0.0 | |
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| No log | 3.0 | 174 | 1.0088 | 0.0077 | 55.7377 | 82.8805 | 915 | 55.7377 | 82.8805 | 915 | 55.7377 | 0.0 | 82.8805 | 0.0 | |
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| No log | 4.0 | 232 | 1.0865 | 0.0077 | 54.4262 | 81.7459 | 915 | 54.4262 | 81.7459 | 915 | 54.4262 | 0.0 | 81.7459 | 0.0 | |
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| No log | 5.0 | 290 | 1.2034 | 0.0077 | 53.7705 | 81.5328 | 915 | 53.7705 | 81.5328 | 915 | 53.7705 | 0.0 | 81.5328 | 0.0 | |
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| No log | 6.0 | 348 | 1.2822 | 0.0077 | 54.2077 | 81.9985 | 915 | 54.2077 | 81.9985 | 915 | 54.2077 | 0.0 | 81.9985 | 0.0 | |
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| No log | 7.0 | 406 | 1.3357 | 0.0077 | 54.2077 | 81.7294 | 915 | 54.2077 | 81.7294 | 915 | 54.2077 | 0.0 | 81.7294 | 0.0 | |
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| No log | 8.0 | 464 | 1.3738 | 0.0077 | 54.6448 | 81.9526 | 915 | 54.6448 | 81.9526 | 915 | 54.6448 | 0.0 | 81.9526 | 0.0 | |
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| 0.4292 | 9.0 | 522 | 1.4215 | 0.0077 | 54.7541 | 81.7385 | 915 | 54.7541 | 81.7385 | 915 | 54.7541 | 0.0 | 81.7385 | 0.0 | |
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| 0.4292 | 10.0 | 580 | 1.4342 | 0.0077 | 53.4426 | 81.3729 | 915 | 53.4426 | 81.3729 | 915 | 53.4426 | 0.0 | 81.3729 | 0.0 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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