camembert-secabilite-regressor
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0136
- Model Preparation Time: 0.0011
- Mse: 0.0137
- Mae: 0.0557
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Mse | Mae |
---|---|---|---|---|---|---|
0.0102 | 1.0 | 108 | 0.0136 | 0.0011 | 0.0137 | 0.0624 |
0.0095 | 2.0 | 216 | 0.0144 | 0.0011 | 0.0144 | 0.0607 |
0.0089 | 3.0 | 324 | 0.0141 | 0.0011 | 0.0141 | 0.0590 |
0.0089 | 4.0 | 432 | 0.0139 | 0.0011 | 0.0140 | 0.0576 |
0.009 | 5.0 | 540 | 0.0138 | 0.0011 | 0.0139 | 0.0568 |
0.0091 | 6.0 | 648 | 0.0136 | 0.0011 | 0.0137 | 0.0561 |
0.0085 | 7.0 | 756 | 0.0136 | 0.0011 | 0.0137 | 0.0557 |
0.0084 | 8.0 | 864 | 0.0136 | 0.0011 | 0.0137 | 0.0557 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0
- Datasets 3.5.0
- Tokenizers 0.21.1
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