nlp
This model is a fine-tuned version of camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0207
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9976
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: 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 160 | 0.0338 | 0.0 | 0.0 | 0.0 | 0.9971 |
No log | 2.0 | 320 | 0.0266 | 0.0 | 0.0 | 0.0 | 0.9977 |
No log | 3.0 | 480 | 0.0230 | 0.0 | 0.0 | 0.0 | 0.9975 |
0.0359 | 4.0 | 640 | 0.0212 | 0.0 | 0.0 | 0.0 | 0.9976 |
0.0359 | 5.0 | 800 | 0.0207 | 0.0 | 0.0 | 0.0 | 0.9976 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1
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Base model
almanach/camembert-base