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---
license: apache-2.0
base_model: BSC-LT/roberta-base-biomedical-clinical-es
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-biomedical-clinical-es-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-biomedical-clinical-es-ner
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.
It achieves the following results on the evaluation set:
- Loss: 0.3813
- Precision: 0.8687
- Recall: 0.8919
- F1: 0.8801
- Accuracy: 0.9374
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 280 | 0.3201 | 0.7961 | 0.8385 | 0.8167 | 0.9130 |
| 0.5051 | 2.0 | 560 | 0.2833 | 0.8245 | 0.8770 | 0.8500 | 0.9282 |
| 0.5051 | 3.0 | 840 | 0.2717 | 0.8459 | 0.8622 | 0.8540 | 0.9262 |
| 0.1434 | 4.0 | 1120 | 0.2782 | 0.8477 | 0.8904 | 0.8685 | 0.9324 |
| 0.1434 | 5.0 | 1400 | 0.3119 | 0.8525 | 0.8993 | 0.8753 | 0.9355 |
| 0.0804 | 6.0 | 1680 | 0.3146 | 0.8639 | 0.8933 | 0.8784 | 0.9366 |
| 0.0804 | 7.0 | 1960 | 0.3211 | 0.8637 | 0.8919 | 0.8776 | 0.9346 |
| 0.0475 | 8.0 | 2240 | 0.3523 | 0.8707 | 0.8978 | 0.8840 | 0.9372 |
| 0.0347 | 9.0 | 2520 | 0.3651 | 0.8434 | 0.8859 | 0.8642 | 0.9335 |
| 0.0347 | 10.0 | 2800 | 0.3663 | 0.8706 | 0.8874 | 0.8789 | 0.9360 |
| 0.0241 | 11.0 | 3080 | 0.3756 | 0.8680 | 0.8963 | 0.8819 | 0.9372 |
| 0.0241 | 12.0 | 3360 | 0.3692 | 0.86 | 0.8919 | 0.8756 | 0.9369 |
| 0.0201 | 13.0 | 3640 | 0.3782 | 0.8631 | 0.8874 | 0.8751 | 0.9360 |
| 0.0201 | 14.0 | 3920 | 0.3820 | 0.8698 | 0.8904 | 0.8799 | 0.9374 |
| 0.0172 | 15.0 | 4200 | 0.3813 | 0.8687 | 0.8919 | 0.8801 | 0.9374 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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