---
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: 1.0367
- Precision: 0.2541
- Recall: 0.4551
- F1: 0.3261
- Accuracy: 0.7718

## 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: 3.5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.2727        | 0.7   | 1064  | 1.1739          | 0.1144    | 0.2850 | 0.1632 | 0.7461   |
| 0.9857        | 1.4   | 2128  | 1.0956          | 0.1626    | 0.3425 | 0.2205 | 0.7620   |
| 0.9233        | 2.1   | 3192  | 1.0081          | 0.1457    | 0.3181 | 0.1999 | 0.7646   |
| 0.8635        | 2.8   | 4256  | 1.0164          | 0.2019    | 0.3945 | 0.2671 | 0.7705   |
| 0.821         | 3.5   | 5320  | 0.9852          | 0.1896    | 0.3827 | 0.2536 | 0.7709   |
| 0.7574        | 4.2   | 6384  | 1.0179          | 0.2230    | 0.4157 | 0.2903 | 0.7714   |
| 0.7725        | 4.9   | 7448  | 1.0378          | 0.2276    | 0.4299 | 0.2976 | 0.7695   |
| 0.7365        | 5.6   | 8512  | 1.0315          | 0.2290    | 0.4354 | 0.3001 | 0.7722   |
| 0.6596        | 6.3   | 9576  | 1.0406          | 0.2475    | 0.4496 | 0.3193 | 0.7723   |
| 0.7028        | 7.0   | 10640 | 1.0367          | 0.2541    | 0.4551 | 0.3261 | 0.7718   |


### Framework versions

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