---
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: 0.7203
- Accuracy: 0.875

## 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    | 2.0791          | 0.075    |
| No log        | 2.0   | 10   | 2.0909          | 0.075    |
| No log        | 3.0   | 15   | 2.0903          | 0.075    |
| No log        | 4.0   | 20   | 2.0790          | 0.075    |
| No log        | 5.0   | 25   | 2.0606          | 0.075    |
| No log        | 6.0   | 30   | 2.0206          | 0.1      |
| No log        | 7.0   | 35   | 1.9780          | 0.25     |
| No log        | 8.0   | 40   | 1.9250          | 0.375    |
| No log        | 9.0   | 45   | 1.8724          | 0.5      |
| No log        | 10.0  | 50   | 1.8129          | 0.525    |
| No log        | 11.0  | 55   | 1.7570          | 0.55     |
| No log        | 12.0  | 60   | 1.7009          | 0.65     |
| No log        | 13.0  | 65   | 1.6472          | 0.625    |
| No log        | 14.0  | 70   | 1.5928          | 0.675    |
| No log        | 15.0  | 75   | 1.5434          | 0.7      |
| No log        | 16.0  | 80   | 1.4880          | 0.675    |
| No log        | 17.0  | 85   | 1.4333          | 0.7      |
| No log        | 18.0  | 90   | 1.3811          | 0.7      |
| No log        | 19.0  | 95   | 1.3339          | 0.7      |
| No log        | 20.0  | 100  | 1.2919          | 0.75     |
| No log        | 21.0  | 105  | 1.2493          | 0.725    |
| No log        | 22.0  | 110  | 1.2091          | 0.725    |
| No log        | 23.0  | 115  | 1.1707          | 0.75     |
| No log        | 24.0  | 120  | 1.1311          | 0.775    |
| No log        | 25.0  | 125  | 1.0946          | 0.825    |
| No log        | 26.0  | 130  | 1.0642          | 0.8      |
| No log        | 27.0  | 135  | 1.0363          | 0.8      |
| No log        | 28.0  | 140  | 1.0172          | 0.8      |
| No log        | 29.0  | 145  | 0.9939          | 0.825    |
| No log        | 30.0  | 150  | 0.9682          | 0.825    |
| No log        | 31.0  | 155  | 0.9443          | 0.8      |
| No log        | 32.0  | 160  | 0.9289          | 0.825    |
| No log        | 33.0  | 165  | 0.9113          | 0.85     |
| No log        | 34.0  | 170  | 0.9017          | 0.85     |
| No log        | 35.0  | 175  | 0.8804          | 0.85     |
| No log        | 36.0  | 180  | 0.8598          | 0.85     |
| No log        | 37.0  | 185  | 0.8484          | 0.825    |
| No log        | 38.0  | 190  | 0.8361          | 0.825    |
| No log        | 39.0  | 195  | 0.8306          | 0.825    |
| No log        | 40.0  | 200  | 0.8242          | 0.825    |
| No log        | 41.0  | 205  | 0.8198          | 0.85     |
| No log        | 42.0  | 210  | 0.8051          | 0.85     |
| No log        | 43.0  | 215  | 0.7854          | 0.85     |
| No log        | 44.0  | 220  | 0.7727          | 0.9      |
| No log        | 45.0  | 225  | 0.7626          | 0.9      |
| No log        | 46.0  | 230  | 0.7579          | 0.9      |
| No log        | 47.0  | 235  | 0.7500          | 0.9      |
| No log        | 48.0  | 240  | 0.7477          | 0.875    |
| No log        | 49.0  | 245  | 0.7517          | 0.85     |
| No log        | 50.0  | 250  | 0.7484          | 0.85     |
| No log        | 51.0  | 255  | 0.7446          | 0.85     |
| No log        | 52.0  | 260  | 0.7414          | 0.85     |
| No log        | 53.0  | 265  | 0.7357          | 0.875    |
| No log        | 54.0  | 270  | 0.7303          | 0.875    |
| No log        | 55.0  | 275  | 0.7249          | 0.875    |
| No log        | 56.0  | 280  | 0.7232          | 0.875    |
| No log        | 57.0  | 285  | 0.7228          | 0.875    |
| No log        | 58.0  | 290  | 0.7215          | 0.875    |
| No log        | 59.0  | 295  | 0.7206          | 0.875    |
| No log        | 60.0  | 300  | 0.7203          | 0.875    |


### Framework versions

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