---
license: apache-2.0
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
tags:
- token-classification
- generated_from_trainer
datasets:
- Rodrigo1771/multi-train-distemist-dev-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: Rodrigo1771/multi-train-distemist-dev-ner
      type: Rodrigo1771/multi-train-distemist-dev-ner
      config: MultiTrainDisTEMISTDevNER
      split: validation
      args: MultiTrainDisTEMISTDevNER
    metrics:
    - name: Precision
      type: precision
      value: 0.32143181611701643
    - name: Recall
      type: recall
      value: 0.8277959756668226
    - name: F1
      type: f1
      value: 0.46305870034683594
    - name: Accuracy
      type: accuracy
      value: 0.8559776451929613
---

<!-- 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. -->

# output

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the Rodrigo1771/multi-train-distemist-dev-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9499
- Precision: 0.3214
- Recall: 0.8278
- F1: 0.4631
- Accuracy: 0.8560

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2596        | 0.9997 | 1701  | 0.4319          | 0.2617    | 0.7866 | 0.3927 | 0.8359   |
| 0.1853        | 2.0    | 3403  | 0.3841          | 0.3142    | 0.7829 | 0.4485 | 0.8645   |
| 0.1254        | 2.9997 | 5104  | 0.6410          | 0.3055    | 0.8088 | 0.4435 | 0.8436   |
| 0.0823        | 4.0    | 6806  | 0.7242          | 0.2964    | 0.8074 | 0.4336 | 0.8436   |
| 0.0597        | 4.9997 | 8507  | 0.7756          | 0.3133    | 0.7948 | 0.4495 | 0.8502   |
| 0.0446        | 6.0    | 10209 | 0.8561          | 0.3137    | 0.8037 | 0.4513 | 0.8483   |
| 0.0325        | 6.9997 | 11910 | 0.9499          | 0.3214    | 0.8278 | 0.4631 | 0.8560   |
| 0.022         | 8.0    | 13612 | 1.0452          | 0.3129    | 0.8222 | 0.4533 | 0.8510   |
| 0.017         | 8.9997 | 15313 | 1.1025          | 0.3133    | 0.8180 | 0.4531 | 0.8524   |
| 0.0135        | 9.9971 | 17010 | 1.1188          | 0.3145    | 0.8224 | 0.4550 | 0.8526   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1