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

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: 1.6618
- Accuracy: 0.425

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 2.0911          | 0.075    |
| No log        | 2.0   | 10   | 2.1008          | 0.05     |
| No log        | 3.0   | 15   | 2.1027          | 0.05     |
| No log        | 4.0   | 20   | 2.0983          | 0.1      |
| No log        | 5.0   | 25   | 2.0928          | 0.125    |
| No log        | 6.0   | 30   | 2.0899          | 0.15     |
| No log        | 7.0   | 35   | 2.0827          | 0.175    |
| No log        | 8.0   | 40   | 2.0689          | 0.175    |
| No log        | 9.0   | 45   | 2.0537          | 0.25     |
| No log        | 10.0  | 50   | 2.0350          | 0.3      |
| No log        | 11.0  | 55   | 2.0110          | 0.325    |
| No log        | 12.0  | 60   | 1.9837          | 0.35     |
| No log        | 13.0  | 65   | 1.9513          | 0.4      |
| No log        | 14.0  | 70   | 1.9203          | 0.4      |
| No log        | 15.0  | 75   | 1.8931          | 0.4      |
| No log        | 16.0  | 80   | 1.8668          | 0.4      |
| No log        | 17.0  | 85   | 1.8440          | 0.4      |
| No log        | 18.0  | 90   | 1.8216          | 0.425    |
| No log        | 19.0  | 95   | 1.7954          | 0.425    |
| No log        | 20.0  | 100  | 1.7735          | 0.425    |
| No log        | 21.0  | 105  | 1.7529          | 0.425    |
| No log        | 22.0  | 110  | 1.7339          | 0.425    |
| No log        | 23.0  | 115  | 1.7168          | 0.425    |
| No log        | 24.0  | 120  | 1.7025          | 0.425    |
| No log        | 25.0  | 125  | 1.6904          | 0.425    |
| No log        | 26.0  | 130  | 1.6798          | 0.425    |
| No log        | 27.0  | 135  | 1.6723          | 0.425    |
| No log        | 28.0  | 140  | 1.6667          | 0.425    |
| No log        | 29.0  | 145  | 1.6632          | 0.425    |
| No log        | 30.0  | 150  | 1.6618          | 0.425    |


### Framework versions

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