BEREL-finetuned-DSS-composition-classification
This model is a fine-tuned version of dicta-il/BEREL on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5561
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 37 | 2.5131 |
| No log | 2.0 | 74 | 2.1557 |
| No log | 3.0 | 111 | 1.9236 |
| No log | 4.0 | 148 | 1.7455 |
| No log | 5.0 | 185 | 1.6608 |
| No log | 6.0 | 222 | 1.5844 |
| No log | 7.0 | 259 | 1.5561 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for yonatanlou/BEREL-finetuned-DSS-composition-classification
Base model
dicta-il/BEREL