---
library_name: transformers
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert-math-classification
  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. -->

# camembert-math-classification

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0166
- F1 Macro: 0.9987
- F1 Weighted: 0.9987
- F1 Correct: 1.0
- F1 Partiel: 0.9980
- F1 Incorrect: 0.9980
- Accuracy: 0.9987

## 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: 32
- eval_batch_size: 64
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Correct | F1 Partiel | F1 Incorrect | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:----------:|:----------:|:------------:|:--------:|
| 0.6561        | 1.0   | 184  | 0.8086          | 0.4912   | 0.4912      | 0.8169     | 0.0204     | 0.6364       | 0.5675   |
| 0.1997        | 2.0   | 368  | 0.1530          | 0.9669   | 0.9669      | 0.9902     | 0.9513     | 0.9592       | 0.9669   |
| 0.0648        | 3.0   | 552  | 0.0360          | 0.9960   | 0.9960      | 1.0        | 0.9940     | 0.9941       | 0.9960   |
| 0.0261        | 4.0   | 736  | 0.0227          | 0.9974   | 0.9974      | 0.9980     | 0.9960     | 0.9980       | 0.9974   |
| 0.0147        | 5.0   | 920  | 0.0166          | 0.9987   | 0.9987      | 1.0        | 0.9980     | 0.9980       | 0.9987   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2