---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_classifier-only_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_classifier-only_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: 0.2602
- Accuracy: 0.875
- Learning Rate: 0.0004

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.9376        | 1.0   | 15   | 1.6974          | 0.3542   | 0.0010 |
| 1.4628        | 2.0   | 30   | 1.4891          | 0.4792   | 0.0010 |
| 1.1834        | 3.0   | 45   | 0.9756          | 0.7083   | 0.0009 |
| 0.9327        | 4.0   | 60   | 0.8686          | 0.6979   | 0.0009 |
| 0.781         | 5.0   | 75   | 0.7231          | 0.7083   | 0.0009 |
| 0.7408        | 6.0   | 90   | 0.5991          | 0.8229   | 0.0009 |
| 0.6046        | 7.0   | 105  | 0.5022          | 0.875    | 0.0009 |
| 0.5957        | 8.0   | 120  | 0.4873          | 0.8021   | 0.0009 |
| 0.5546        | 9.0   | 135  | 0.4919          | 0.8125   | 0.0008 |
| 0.5204        | 10.0  | 150  | 0.4814          | 0.8021   | 0.0008 |
| 0.4636        | 11.0  | 165  | 0.3945          | 0.8542   | 0.0008 |
| 0.4405        | 12.0  | 180  | 0.4338          | 0.8229   | 0.0008 |
| 0.4805        | 13.0  | 195  | 0.3747          | 0.8854   | 0.0008 |
| 0.39          | 14.0  | 210  | 0.3946          | 0.8854   | 0.0008 |
| 0.3982        | 15.0  | 225  | 0.3480          | 0.8438   | 0.0008 |
| 0.3967        | 16.0  | 240  | 0.3188          | 0.9271   | 0.0007 |
| 0.3836        | 17.0  | 255  | 0.4498          | 0.7812   | 0.0007 |
| 0.3764        | 18.0  | 270  | 0.2861          | 0.8958   | 0.0007 |
| 0.3387        | 19.0  | 285  | 0.2953          | 0.9062   | 0.0007 |
| 0.3749        | 20.0  | 300  | 0.2771          | 0.9062   | 0.0007 |
| 0.3353        | 21.0  | 315  | 0.3058          | 0.8958   | 0.0007 |
| 0.3523        | 22.0  | 330  | 0.2710          | 0.9062   | 0.0006 |
| 0.3383        | 23.0  | 345  | 0.2597          | 0.9167   | 0.0006 |
| 0.3223        | 24.0  | 360  | 0.3180          | 0.8854   | 0.0006 |
| 0.3644        | 25.0  | 375  | 0.2712          | 0.9062   | 0.0006 |
| 0.3015        | 26.0  | 390  | 0.2775          | 0.9062   | 0.0006 |
| 0.3186        | 27.0  | 405  | 0.2386          | 0.9375   | 0.0006 |
| 0.2915        | 28.0  | 420  | 0.3227          | 0.8958   | 0.0005 |
| 0.3049        | 29.0  | 435  | 0.2908          | 0.9167   | 0.0005 |
| 0.3131        | 30.0  | 450  | 0.2921          | 0.9062   | 0.0005 |
| 0.3187        | 31.0  | 465  | 0.2733          | 0.9062   | 0.0005 |
| 0.3051        | 32.0  | 480  | 0.2850          | 0.9062   | 0.0005 |
| 0.2775        | 33.0  | 495  | 0.2621          | 0.9062   | 0.0005 |
| 0.3331        | 34.0  | 510  | 0.2742          | 0.9167   | 0.0004 |
| 0.2854        | 35.0  | 525  | 0.3128          | 0.8854   | 0.0004 |
| 0.294         | 36.0  | 540  | 0.2455          | 0.9167   | 0.0004 |
| 0.2662        | 37.0  | 555  | 0.2602          | 0.875    | 0.0004 |


### Framework versions

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