---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_qlora-8bit_fr
  results: []
---

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# camembert_ccnet_classification_tools_qlora-8bit_fr

This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co./camembert/camembert-base-ccnet) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4541
- Accuracy: 0.825
- Learning Rate: 0.0

## 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: 0.0001
- train_batch_size: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.5754        | 1.0   | 7    | 1.4661          | 0.85     | 0.0001 |
| 1.5602        | 2.0   | 14   | 1.4618          | 0.85     | 0.0000 |
| 1.5649        | 3.0   | 21   | 1.4541          | 0.825    | 0.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1