---
license: apache-2.0
base_model: pabRomero/BERT-full-finetuned-ner-pablo
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT-full-finetuned-ner-pablo
  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. -->

# BERT-full-finetuned-ner-pablo

This model is a fine-tuned version of [pabRomero/BERT-full-finetuned-ner-pablo](https://huggingface.co/pabRomero/BERT-full-finetuned-ner-pablo) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1343
- Precision: 0.7987
- Recall: 0.7855
- F1: 0.7920
- Accuracy: 0.9688

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1038        | 0.9998 | 2608 | 0.1377          | 0.7579    | 0.7370 | 0.7473 | 0.9645   |
| 0.0715        | 2.0    | 5217 | 0.1353          | 0.7700    | 0.7625 | 0.7663 | 0.9667   |
| 0.0477        | 2.9994 | 7824 | 0.1343          | 0.7987    | 0.7855 | 0.7920 | 0.9688   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1