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---
base_model: dccuchile/tulio-chilean-spanish-bert
license: cc-by-4.0
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: not-ner-v2
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. -->
# not-ner-v2
This model is a fine-tuned version of [dccuchile/tulio-chilean-spanish-bert](https://huggingface.co/dccuchile/tulio-chilean-spanish-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0838
- Accuracy: 0.9727
- Precision: 0.9723
- Recall: 0.9727
- F1: 0.9724
## 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: 32
- eval_batch_size: 8
- 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 | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1679 | 0.1595 | 250 | 0.1431 | 0.9555 | 0.9546 | 0.9555 | 0.9549 |
| 0.1291 | 0.3191 | 500 | 0.1328 | 0.9595 | 0.9583 | 0.9595 | 0.9586 |
| 0.1055 | 0.4786 | 750 | 0.0925 | 0.9653 | 0.9648 | 0.9653 | 0.9650 |
| 0.1044 | 0.6382 | 1000 | 0.1415 | 0.9630 | 0.9619 | 0.9630 | 0.9615 |
| 0.1094 | 0.7977 | 1250 | 0.1030 | 0.9630 | 0.9624 | 0.9630 | 0.9612 |
| 0.0927 | 0.9572 | 1500 | 0.0878 | 0.9710 | 0.9706 | 0.9710 | 0.9707 |
| 0.0836 | 1.1168 | 1750 | 0.1265 | 0.9663 | 0.9666 | 0.9663 | 0.9665 |
| 0.0651 | 1.2763 | 2000 | 0.1025 | 0.9709 | 0.9702 | 0.9709 | 0.9704 |
| 0.0637 | 1.4359 | 2250 | 0.0998 | 0.9676 | 0.9668 | 0.9676 | 0.9667 |
| 0.0713 | 1.5954 | 2500 | 0.0838 | 0.9727 | 0.9723 | 0.9727 | 0.9724 |
| 0.0561 | 1.7549 | 2750 | 0.0905 | 0.9722 | 0.9722 | 0.9722 | 0.9722 |
| 0.058 | 1.9145 | 3000 | 0.1030 | 0.9707 | 0.9701 | 0.9707 | 0.9702 |
| 0.0531 | 2.0740 | 3250 | 0.1066 | 0.9714 | 0.9710 | 0.9714 | 0.9711 |
| 0.0398 | 2.2336 | 3500 | 0.1035 | 0.9722 | 0.9721 | 0.9722 | 0.9721 |
| 0.0444 | 2.3931 | 3750 | 0.1009 | 0.9728 | 0.9725 | 0.9728 | 0.9726 |
| 0.037 | 2.5526 | 4000 | 0.1068 | 0.9725 | 0.9721 | 0.9725 | 0.9722 |
| 0.0261 | 2.7122 | 4250 | 0.1192 | 0.9735 | 0.9731 | 0.9735 | 0.9732 |
| 0.0266 | 2.8717 | 4500 | 0.1191 | 0.9732 | 0.9727 | 0.9732 | 0.9729 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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