---
library_name: transformers
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# results

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4448
- Accuracy: 0.9239
- F1: 0.9226

## 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: 8
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2178        | 1.0   | 992  | 0.2705          | 0.9143   | 0.9160 |
| 0.1932        | 2.0   | 1984 | 0.2340          | 0.9340   | 0.9323 |
| 0.157         | 3.0   | 2976 | 0.2491          | 0.9266   | 0.9262 |
| 0.1432        | 4.0   | 3968 | 0.2768          | 0.9261   | 0.9251 |
| 0.0788        | 5.0   | 4960 | 0.3313          | 0.9254   | 0.9246 |
| 0.0669        | 6.0   | 5952 | 0.3403          | 0.9271   | 0.9263 |
| 0.0934        | 7.0   | 6944 | 0.4120          | 0.9239   | 0.9224 |
| 0.0579        | 8.0   | 7936 | 0.4046          | 0.9231   | 0.9226 |
| 0.0364        | 9.0   | 8928 | 0.4379          | 0.9234   | 0.9221 |
| 0.0985        | 10.0  | 9920 | 0.4448          | 0.9239   | 0.9226 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1