hscore-balanced
This model is a fine-tuned version of camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2353
- Accuracy: 0.9274
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: 8.497821083760116e-06
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1801 | 1.0 | 1643 | 0.2273 | 0.9200 |
0.3525 | 2.0 | 3286 | 0.2126 | 0.9266 |
0.0821 | 3.0 | 4929 | 0.2383 | 0.9291 |
0.4058 | 4.0 | 6572 | 0.2149 | 0.9283 |
0.2079 | 5.0 | 8215 | 0.2353 | 0.9274 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
almanach/camembert-base