---
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