text-classification
This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4197
- Accuracy: 0.4503
Model description
Este modelo emplea un algoritmo de clasificación de textos. Emplea el modelo Electricidad para tokenizar el texto.
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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 388 | 1.3400 | 0.4052 |
| 1.3886 | 2.0 | 776 | 1.2878 | 0.4387 |
| 0.9608 | 3.0 | 1164 | 1.4197 | 0.4503 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for sanar085/text-classification
Base model
mrm8488/electricidad-base-discriminator