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---
license: cc-by-4.0
base_model: bertin-project/bertin-roberta-base-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-model-Bertin-Area
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. -->
# my-model-Bertin-Area
This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0081
- Accuracy: 0.5540
- F1: 0.5447
- Precision: 0.6083
- Recall: 0.5540
## 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: 30
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.8057 | 1.0 | 22 | 1.6694 | 0.3094 | 0.1478 | 0.0971 | 0.3094 |
| 1.6881 | 2.0 | 44 | 1.5645 | 0.3741 | 0.2735 | 0.2381 | 0.3741 |
| 1.4559 | 3.0 | 66 | 1.3527 | 0.5612 | 0.4682 | 0.4308 | 0.5612 |
| 1.0349 | 4.0 | 88 | 1.2698 | 0.5108 | 0.4710 | 0.5251 | 0.5108 |
| 0.5922 | 5.0 | 110 | 1.3228 | 0.5396 | 0.5357 | 0.5761 | 0.5396 |
| 0.3388 | 6.0 | 132 | 1.3421 | 0.5324 | 0.5465 | 0.6025 | 0.5324 |
| 0.1581 | 7.0 | 154 | 1.6898 | 0.5396 | 0.5210 | 0.6214 | 0.5396 |
| 0.0756 | 8.0 | 176 | 1.5726 | 0.5971 | 0.5805 | 0.5852 | 0.5971 |
| 0.0485 | 9.0 | 198 | 1.6224 | 0.5971 | 0.6071 | 0.6341 | 0.5971 |
| 0.0238 | 10.0 | 220 | 1.9468 | 0.5683 | 0.5592 | 0.6588 | 0.5683 |
| 0.0111 | 11.0 | 242 | 1.8085 | 0.5540 | 0.5505 | 0.5994 | 0.5540 |
| 0.0043 | 12.0 | 264 | 1.7379 | 0.5755 | 0.5672 | 0.6076 | 0.5755 |
| 0.0029 | 13.0 | 286 | 1.9594 | 0.5612 | 0.5527 | 0.6202 | 0.5612 |
| 0.0024 | 14.0 | 308 | 2.0399 | 0.5683 | 0.5606 | 0.6429 | 0.5683 |
| 0.0021 | 15.0 | 330 | 1.9871 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
| 0.002 | 16.0 | 352 | 1.9870 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
| 0.0018 | 17.0 | 374 | 1.9927 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
| 0.0018 | 18.0 | 396 | 2.0027 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
| 0.0017 | 19.0 | 418 | 2.0077 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
| 0.0017 | 20.0 | 440 | 2.0081 | 0.5540 | 0.5447 | 0.6083 | 0.5540 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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