---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2
  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_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2

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: 2.0965
- Accuracy: 0.1042
- Learning Rate: 0.0008

## 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: 0.001
- 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 | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.1119        | 1.0   | 15   | 2.1246          | 0.1042   | 0.0010 |
| 2.0909        | 2.0   | 30   | 2.1521          | 0.0938   | 0.0010 |
| 2.1043        | 3.0   | 45   | 2.0959          | 0.0938   | 0.0009 |
| 2.0866        | 4.0   | 60   | 2.1143          | 0.0938   | 0.0009 |
| 2.0746        | 5.0   | 75   | 2.1063          | 0.1354   | 0.0009 |
| 2.0753        | 6.0   | 90   | 2.1266          | 0.0938   | 0.0009 |
| 2.0793        | 7.0   | 105  | 2.1177          | 0.1146   | 0.0009 |
| 2.0844        | 8.0   | 120  | 2.0959          | 0.1354   | 0.0009 |
| 2.0855        | 9.0   | 135  | 2.1072          | 0.0938   | 0.0008 |
| 2.0805        | 10.0  | 150  | 2.1128          | 0.0938   | 0.0008 |
| 2.079         | 11.0  | 165  | 2.1027          | 0.1354   | 0.0008 |
| 2.0855        | 12.0  | 180  | 2.1164          | 0.0938   | 0.0008 |
| 2.0745        | 13.0  | 195  | 2.0965          | 0.1042   | 0.0008 |


### Framework versions

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