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---
tags:
- generated_from_trainer
base_model: dccuchile/bert-base-spanish-wwm-cased
metrics:
- accuracy
- f1
- recall
model-index:
- name: ClasificadorV2
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. -->
# ClasificadorV2
This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1411
- Accuracy: 0.5708
- Off By One Accuracy: 0.9434
- F1: 0.5724
- Recall: 0.5708
## 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: 2e-05
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Off By One Accuracy | F1 | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------------:|:------:|:------:|
| 1.2177 | 0.3333 | 500 | 1.0309 | 0.5426 | 0.93 | 0.5414 | 0.5426 |
| 1.011 | 0.6667 | 1000 | 0.9836 | 0.565 | 0.9336 | 0.5485 | 0.565 |
| 0.9833 | 1.0 | 1500 | 0.9664 | 0.5752 | 0.9448 | 0.5704 | 0.5752 |
| 0.9004 | 1.3333 | 2000 | 0.9566 | 0.5728 | 0.9476 | 0.5743 | 0.5728 |
| 0.8974 | 1.6667 | 2500 | 0.9583 | 0.5782 | 0.9472 | 0.5784 | 0.5782 |
| 0.8912 | 2.0 | 3000 | 0.9480 | 0.5816 | 0.9498 | 0.5768 | 0.5816 |
| 0.7935 | 2.3333 | 3500 | 0.9768 | 0.582 | 0.9472 | 0.5800 | 0.582 |
| 0.7898 | 2.6667 | 4000 | 0.9831 | 0.5716 | 0.9426 | 0.5715 | 0.5716 |
| 0.7801 | 3.0 | 4500 | 0.9969 | 0.5736 | 0.9514 | 0.5759 | 0.5736 |
| 0.6714 | 3.3333 | 5000 | 1.0782 | 0.5826 | 0.9392 | 0.5795 | 0.5826 |
| 0.6783 | 3.6667 | 5500 | 1.0672 | 0.5724 | 0.9456 | 0.5752 | 0.5724 |
| 0.6764 | 4.0 | 6000 | 1.0762 | 0.567 | 0.9458 | 0.5708 | 0.567 |
| 0.5986 | 4.3333 | 6500 | 1.1349 | 0.5698 | 0.9412 | 0.5684 | 0.5698 |
| 0.5887 | 4.6667 | 7000 | 1.1335 | 0.5706 | 0.9398 | 0.5716 | 0.5706 |
| 0.5798 | 5.0 | 7500 | 1.1411 | 0.5708 | 0.9434 | 0.5724 | 0.5708 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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