metadata
base_model: camembert/camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: classificateur-intention_camembert
results: []
classificateur-intention_camembert
This model is a fine-tuned version of camembert/camembert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5463
- Accuracy: 0.8889
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: 0.0002
- 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
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7517 | 2.0 | 10 | 0.4700 | 0.8889 |
| 0.2834 | 4.0 | 20 | 0.3313 | 0.8889 |
| 0.0488 | 6.0 | 30 | 0.3528 | 0.8889 |
| 0.0181 | 8.0 | 40 | 0.6355 | 0.8889 |
| 0.0079 | 10.0 | 50 | 0.6676 | 0.8889 |
| 0.0437 | 12.0 | 60 | 0.5817 | 0.8889 |
| 0.0049 | 14.0 | 70 | 0.4499 | 0.8889 |
| 0.0192 | 16.0 | 80 | 0.5162 | 0.8889 |
| 0.0045 | 18.0 | 90 | 0.5420 | 0.8889 |
| 0.0042 | 20.0 | 100 | 0.5463 | 0.8889 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2