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--- |
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license: apache-2.0 |
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base_model: BSC-LT/roberta-base-biomedical-clinical-es |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds |
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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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# final-ft__roberta-base-biomedical-clinical-es__70k-ultrasounds |
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This model is a fine-tuned version of [BSC-LT/roberta-base-biomedical-clinical-es](https://huggingface.co/BSC-LT/roberta-base-biomedical-clinical-es) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5971 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 20 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| No log | 0.9978 | 229 | 0.9388 | |
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| No log | 2.0 | 459 | 0.8139 | |
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| No log | 2.9978 | 688 | 0.7544 | |
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| 0.9622 | 4.0 | 918 | 0.7302 | |
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| 0.9622 | 4.9978 | 1147 | 0.6878 | |
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| 0.9622 | 6.0 | 1377 | 0.6754 | |
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| 0.9622 | 6.9978 | 1606 | 0.6625 | |
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| 0.715 | 8.0 | 1836 | 0.6431 | |
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| 0.715 | 8.9978 | 2065 | 0.6278 | |
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| 0.715 | 10.0 | 2295 | 0.6361 | |
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| 0.715 | 10.9978 | 2524 | 0.6296 | |
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| 0.6597 | 12.0 | 2754 | 0.6164 | |
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| 0.6597 | 12.9978 | 2983 | 0.6117 | |
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| 0.6597 | 14.0 | 3213 | 0.6052 | |
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| 0.6597 | 14.9978 | 3442 | 0.6064 | |
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| 0.6354 | 16.0 | 3672 | 0.6225 | |
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| 0.6354 | 16.9978 | 3901 | 0.5974 | |
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| 0.6354 | 18.0 | 4131 | 0.6010 | |
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| 0.6354 | 18.9978 | 4360 | 0.5816 | |
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| 0.6354 | 19.9564 | 4580 | 0.5971 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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