---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- disease
metrics:
- precision
- recall
- f1
- accuracy
base_model: plncmm/roberta-clinical-wl-es
model-index:
- name: spanish-disease-tagger
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: disease
      type: disease
      config: disease
      split: train
      args: disease
    metrics:
    - type: precision
      value: 0.8385373870172556
      name: Precision
    - type: recall
      value: 0.8711054204011951
      name: Recall
    - type: f1
      value: 0.8545111994975926
      name: F1
    - type: accuracy
      value: 0.9487721041951381
      name: Accuracy
---

<!-- 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. -->

# spanish-disease-tagger

This model is a fine-tuned version of [plncmm/roberta-clinical-wl-es](https://huggingface.co./plncmm/roberta-clinical-wl-es) on the disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1786
- Precision: 0.8385
- Recall: 0.8711
- F1: 0.8545
- Accuracy: 0.9488

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2217        | 1.0   | 502  | 0.1698          | 0.8142    | 0.8587 | 0.8359 | 0.9437   |
| 0.1203        | 2.0   | 1004 | 0.1735          | 0.8513    | 0.8528 | 0.8520 | 0.9473   |
| 0.093         | 3.0   | 1506 | 0.1786          | 0.8385    | 0.8711 | 0.8545 | 0.9488   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2