metadata
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: trainer_output
results: []
trainer_output
This model is a fine-tuned version of almanach/camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2064
- Accuracy: 0.9119
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
- distributed_type: multi-GPU
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 30 | 0.3752 | 0.8742 |
| No log | 2.0 | 60 | 0.3463 | 0.8742 |
| No log | 3.0 | 90 | 0.2804 | 0.8742 |
| No log | 4.0 | 120 | 0.2925 | 0.8805 |
| No log | 5.0 | 150 | 0.2599 | 0.8868 |
| No log | 6.0 | 180 | 0.2527 | 0.8931 |
| No log | 7.0 | 210 | 0.2176 | 0.8994 |
| No log | 8.0 | 240 | 0.2105 | 0.8994 |
| No log | 9.0 | 270 | 0.2096 | 0.9119 |
| No log | 10.0 | 300 | 0.2064 | 0.9119 |
Framework versions
- Transformers 5.5.3
- Pytorch 2.7.0+cu126
- Datasets 4.8.4
- Tokenizers 0.22.2