camembert-chronicle-start-detection-v3
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6064
- Accuracy: 0.7090
- F1: 0.8297
- Precision: 0.7090
- Recall: 1.0
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 112 | 0.6064 | 0.7090 | 0.8297 | 0.7090 | 1.0 |
| No log | 2.0 | 224 | 0.5962 | 0.7090 | 0.8297 | 0.7090 | 1.0 |
| No log | 3.0 | 336 | 0.5957 | 0.7090 | 0.8297 | 0.7090 | 1.0 |
| No log | 4.0 | 448 | 0.5972 | 0.7090 | 0.8297 | 0.7090 | 1.0 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.8.0
- Tokenizers 0.22.2