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---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-biomedical-es
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biomedical-roberta-finetuned-iomed_task
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. -->
# biomedical-roberta-finetuned-iomed_task
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0582
- Precision: 0.2269
- Recall: 0.4283
- F1: 0.2966
- Accuracy: 0.7695
## 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: 2.1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.2536 | 2.0 | 1520 | 1.2135 | 0.1082 | 0.2685 | 0.1542 | 0.7422 |
| 1.0249 | 4.0 | 3040 | 1.0510 | 0.1448 | 0.3244 | 0.2002 | 0.7650 |
| 0.9 | 6.0 | 4560 | 1.0098 | 0.1587 | 0.3512 | 0.2186 | 0.7694 |
| 0.8002 | 8.0 | 6080 | 1.0143 | 0.1835 | 0.3795 | 0.2474 | 0.7664 |
| 0.7195 | 10.0 | 7600 | 1.0173 | 0.2007 | 0.4055 | 0.2685 | 0.7691 |
| 0.693 | 12.0 | 9120 | 1.0218 | 0.1991 | 0.4079 | 0.2676 | 0.7683 |
| 0.6139 | 14.0 | 10640 | 1.0394 | 0.2063 | 0.4071 | 0.2738 | 0.7672 |
| 0.616 | 16.0 | 12160 | 1.0376 | 0.2141 | 0.4142 | 0.2823 | 0.7695 |
| 0.5911 | 18.0 | 13680 | 1.0491 | 0.2240 | 0.4268 | 0.2938 | 0.7697 |
| 0.6042 | 20.0 | 15200 | 1.0582 | 0.2269 | 0.4283 | 0.2966 | 0.7695 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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