gs-aristoBERTo
This model is a fine-tuned version of Jacobo/aristoBERTo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8409
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7844 | 1.0 | 2476 | 2.3632 |
| 2.3842 | 2.0 | 4952 | 2.1711 |
| 2.2331 | 3.0 | 7428 | 2.0865 |
| 2.1379 | 4.0 | 9904 | 2.0062 |
| 2.0648 | 5.0 | 12380 | 1.9434 |
| 2.0067 | 6.0 | 14856 | 1.9069 |
| 1.9619 | 7.0 | 17332 | 1.8962 |
| 1.9311 | 8.0 | 19808 | 1.8644 |
| 1.9096 | 9.0 | 22284 | 1.8564 |
| 1.8867 | 10.0 | 24760 | 1.8486 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for CNR-ILC/gs-aristoBERTo
Base model
Jacobo/aristoBERTo