---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_classification_tools_qlora_fr
  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_classification_tools_qlora_fr

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: 0.7280
- Accuracy: 0.85

## 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: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 2.0968          | 0.075    |
| No log        | 2.0   | 10   | 2.1103          | 0.075    |
| No log        | 3.0   | 15   | 2.1119          | 0.075    |
| No log        | 4.0   | 20   | 2.1045          | 0.1      |
| No log        | 5.0   | 25   | 2.0948          | 0.125    |
| No log        | 6.0   | 30   | 2.0586          | 0.125    |
| No log        | 7.0   | 35   | 2.0199          | 0.2      |
| No log        | 8.0   | 40   | 1.9633          | 0.25     |
| No log        | 9.0   | 45   | 1.9075          | 0.35     |
| No log        | 10.0  | 50   | 1.8445          | 0.5      |
| No log        | 11.0  | 55   | 1.7872          | 0.55     |
| No log        | 12.0  | 60   | 1.7288          | 0.6      |
| No log        | 13.0  | 65   | 1.6744          | 0.625    |
| No log        | 14.0  | 70   | 1.6192          | 0.65     |
| No log        | 15.0  | 75   | 1.5612          | 0.65     |
| No log        | 16.0  | 80   | 1.5041          | 0.65     |
| No log        | 17.0  | 85   | 1.4466          | 0.7      |
| No log        | 18.0  | 90   | 1.3910          | 0.675    |
| No log        | 19.0  | 95   | 1.3369          | 0.7      |
| No log        | 20.0  | 100  | 1.2929          | 0.725    |
| No log        | 21.0  | 105  | 1.2470          | 0.725    |
| No log        | 22.0  | 110  | 1.2048          | 0.725    |
| No log        | 23.0  | 115  | 1.1597          | 0.725    |
| No log        | 24.0  | 120  | 1.1148          | 0.775    |
| No log        | 25.0  | 125  | 1.0787          | 0.775    |
| No log        | 26.0  | 130  | 1.0485          | 0.775    |
| No log        | 27.0  | 135  | 1.0222          | 0.75     |
| No log        | 28.0  | 140  | 0.9954          | 0.8      |
| No log        | 29.0  | 145  | 0.9714          | 0.85     |
| No log        | 30.0  | 150  | 0.9442          | 0.825    |
| No log        | 31.0  | 155  | 0.9201          | 0.85     |
| No log        | 32.0  | 160  | 0.9032          | 0.85     |
| No log        | 33.0  | 165  | 0.8843          | 0.85     |
| No log        | 34.0  | 170  | 0.8739          | 0.85     |
| No log        | 35.0  | 175  | 0.8527          | 0.85     |
| No log        | 36.0  | 180  | 0.8312          | 0.85     |
| No log        | 37.0  | 185  | 0.8193          | 0.85     |
| No log        | 38.0  | 190  | 0.8079          | 0.85     |
| No log        | 39.0  | 195  | 0.8015          | 0.85     |
| No log        | 40.0  | 200  | 0.7962          | 0.85     |
| No log        | 41.0  | 205  | 0.7958          | 0.85     |
| No log        | 42.0  | 210  | 0.7846          | 0.85     |
| No log        | 43.0  | 215  | 0.7652          | 0.85     |
| No log        | 44.0  | 220  | 0.7536          | 0.85     |
| No log        | 45.0  | 225  | 0.7451          | 0.85     |
| No log        | 46.0  | 230  | 0.7377          | 0.85     |
| No log        | 47.0  | 235  | 0.7327          | 0.85     |
| No log        | 48.0  | 240  | 0.7310          | 0.85     |
| No log        | 49.0  | 245  | 0.7312          | 0.85     |
| No log        | 50.0  | 250  | 0.7280          | 0.85     |


### Framework versions

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