---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-clinical-plncmm-large-20
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-finetuned-ner-clinical-plncmm-large-20

This model is a fine-tuned version of [plncmm/beto-clinical-wl-es](https://huggingface.co./plncmm/beto-clinical-wl-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2349
- Precision: 0.7664
- Recall: 0.8337
- F1: 0.7986
- Accuracy: 0.9349

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6258        | 1.0   | 857  | 0.2335          | 0.7199    | 0.8041 | 0.7597 | 0.9257   |
| 0.1764        | 2.0   | 1714 | 0.2308          | 0.7521    | 0.8277 | 0.7881 | 0.9319   |
| 0.1117        | 3.0   | 2571 | 0.2349          | 0.7664    | 0.8337 | 0.7986 | 0.9349   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3