---
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: 1.0160
- Precision: 0.1934
- Recall: 0.3953
- F1: 0.2597
- Accuracy: 0.7681

## 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: 2.2e-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: 13

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.1178        | 1.3   | 988  | 1.3039          | 0.0802    | 0.2102 | 0.1161 | 0.7321   |
| 1.2448        | 2.6   | 1976 | 1.1444          | 0.1161    | 0.2811 | 0.1643 | 0.7568   |
| 1.0297        | 3.9   | 2964 | 1.0724          | 0.1484    | 0.3299 | 0.2047 | 0.7658   |
| 0.9496        | 5.2   | 3952 | 1.0342          | 0.1676    | 0.3583 | 0.2284 | 0.7685   |
| 0.88          | 6.5   | 4940 | 1.0465          | 0.1805    | 0.3795 | 0.2446 | 0.7660   |
| 0.8168        | 7.8   | 5928 | 1.0253          | 0.1713    | 0.3638 | 0.2329 | 0.7624   |
| 0.7863        | 9.1   | 6916 | 1.0293          | 0.1754    | 0.3622 | 0.2364 | 0.7641   |
| 0.784         | 10.4  | 7904 | 1.0159          | 0.1920    | 0.3890 | 0.2571 | 0.7648   |
| 0.7161        | 11.7  | 8892 | 1.0121          | 0.1853    | 0.3819 | 0.2495 | 0.7654   |
| 0.7629        | 13.0  | 9880 | 1.0160          | 0.1934    | 0.3953 | 0.2597 | 0.7681   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3