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---
library_name: transformers
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mi-super-modelo
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. -->
# mi-super-modelo
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3218
- Accuracy: 0.87
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7166 | 0.04 | 5 | 0.6899 | 0.5 |
| 0.6804 | 0.08 | 10 | 0.6806 | 0.505 |
| 0.6756 | 0.12 | 15 | 0.6625 | 0.565 |
| 0.6527 | 0.16 | 20 | 0.6229 | 0.67 |
| 0.6245 | 0.2 | 25 | 0.6537 | 0.585 |
| 0.6079 | 0.24 | 30 | 0.5368 | 0.76 |
| 0.5977 | 0.28 | 35 | 0.4603 | 0.83 |
| 0.3683 | 0.32 | 40 | 0.5971 | 0.71 |
| 0.3948 | 0.36 | 45 | 0.4346 | 0.815 |
| 0.4459 | 0.4 | 50 | 0.4177 | 0.81 |
| 0.5583 | 0.44 | 55 | 0.3364 | 0.855 |
| 0.5495 | 0.48 | 60 | 0.3367 | 0.865 |
| 0.1608 | 0.52 | 65 | 0.3992 | 0.825 |
| 0.4232 | 0.56 | 70 | 0.3484 | 0.835 |
| 0.6385 | 0.6 | 75 | 0.3930 | 0.86 |
| 0.2918 | 0.64 | 80 | 0.3389 | 0.86 |
| 0.2137 | 0.68 | 85 | 0.3272 | 0.865 |
| 0.419 | 0.72 | 90 | 0.3188 | 0.885 |
| 0.2032 | 0.76 | 95 | 0.3158 | 0.87 |
| 0.226 | 0.8 | 100 | 0.3204 | 0.87 |
| 0.2525 | 0.84 | 105 | 0.3398 | 0.83 |
| 0.2573 | 0.88 | 110 | 0.3494 | 0.85 |
| 0.3895 | 0.92 | 115 | 0.3368 | 0.835 |
| 0.2776 | 0.96 | 120 | 0.3241 | 0.87 |
| 0.2487 | 1.0 | 125 | 0.3218 | 0.87 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1
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