---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_classifier-only_fr_lr1e-3_V3
  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_V3

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: 0.1260
- Accuracy: 0.9524
- Learning Rate: 0.0

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.7785        | 1.0   | 14   | 1.5198          | 0.4643   | 0.0010 |
| 1.3586        | 2.0   | 28   | 1.0475          | 0.7381   | 0.0010 |
| 1.0682        | 3.0   | 42   | 0.7517          | 0.7976   | 0.0009 |
| 0.7986        | 4.0   | 56   | 0.7405          | 0.7262   | 0.0009 |
| 0.6711        | 5.0   | 70   | 0.6039          | 0.7976   | 0.0009 |
| 0.6062        | 6.0   | 84   | 0.4750          | 0.8333   | 0.0009 |
| 0.5263        | 7.0   | 98   | 0.3627          | 0.8929   | 0.0009 |
| 0.4188        | 8.0   | 112  | 0.3923          | 0.8452   | 0.0009 |
| 0.4206        | 9.0   | 126  | 0.3147          | 0.9048   | 0.0008 |
| 0.5178        | 10.0  | 140  | 0.3345          | 0.8571   | 0.0008 |
| 0.3435        | 11.0  | 154  | 0.3869          | 0.8095   | 0.0008 |
| 0.3486        | 12.0  | 168  | 0.2324          | 0.9405   | 0.0008 |
| 0.3507        | 13.0  | 182  | 0.2324          | 0.9286   | 0.0008 |
| 0.379         | 14.0  | 196  | 0.2336          | 0.9048   | 0.0008 |
| 0.3516        | 15.0  | 210  | 0.3526          | 0.8571   | 0.0008 |
| 0.3349        | 16.0  | 224  | 0.2204          | 0.9286   | 0.0007 |
| 0.2979        | 17.0  | 238  | 0.2769          | 0.9167   | 0.0007 |
| 0.2981        | 18.0  | 252  | 0.2374          | 0.9048   | 0.0007 |
| 0.2902        | 19.0  | 266  | 0.2410          | 0.9405   | 0.0007 |
| 0.3779        | 20.0  | 280  | 0.2106          | 0.9167   | 0.0007 |
| 0.2486        | 21.0  | 294  | 0.2172          | 0.9405   | 0.0007 |
| 0.2773        | 22.0  | 308  | 0.1927          | 0.9286   | 0.0006 |
| 0.2685        | 23.0  | 322  | 0.1876          | 0.9524   | 0.0006 |
| 0.2416        | 24.0  | 336  | 0.1924          | 0.9286   | 0.0006 |
| 0.2369        | 25.0  | 350  | 0.1686          | 0.9405   | 0.0006 |
| 0.2334        | 26.0  | 364  | 0.2043          | 0.9048   | 0.0006 |
| 0.223         | 27.0  | 378  | 0.1836          | 0.9405   | 0.0006 |
| 0.3389        | 28.0  | 392  | 0.2298          | 0.9167   | 0.0005 |
| 0.2863        | 29.0  | 406  | 0.2005          | 0.9167   | 0.0005 |
| 0.2573        | 30.0  | 420  | 0.1696          | 0.9405   | 0.0005 |
| 0.2192        | 31.0  | 434  | 0.1853          | 0.9286   | 0.0005 |
| 0.2388        | 32.0  | 448  | 0.1546          | 0.9286   | 0.0005 |
| 0.2461        | 33.0  | 462  | 0.1649          | 0.9286   | 0.0005 |
| 0.303         | 34.0  | 476  | 0.1588          | 0.9405   | 0.0004 |
| 0.2262        | 35.0  | 490  | 0.1524          | 0.9405   | 0.0004 |
| 0.3037        | 36.0  | 504  | 0.1469          | 0.9405   | 0.0004 |
| 0.2268        | 37.0  | 518  | 0.1387          | 0.9524   | 0.0004 |
| 0.2315        | 38.0  | 532  | 0.1896          | 0.9405   | 0.0004 |
| 0.2247        | 39.0  | 546  | 0.1572          | 0.9524   | 0.0003 |
| 0.1841        | 40.0  | 560  | 0.1512          | 0.9524   | 0.0003 |
| 0.2357        | 41.0  | 574  | 0.1501          | 0.9405   | 0.0003 |
| 0.2186        | 42.0  | 588  | 0.1642          | 0.9286   | 0.0003 |
| 0.2437        | 43.0  | 602  | 0.1438          | 0.9405   | 0.0003 |
| 0.2399        | 44.0  | 616  | 0.1835          | 0.9405   | 0.0003 |
| 0.2589        | 45.0  | 630  | 0.1565          | 0.9524   | 0.0003 |
| 0.2306        | 46.0  | 644  | 0.1868          | 0.9286   | 0.0002 |
| 0.2159        | 47.0  | 658  | 0.1369          | 0.9524   | 0.0002 |
| 0.212         | 48.0  | 672  | 0.1238          | 0.9524   | 0.0002 |
| 0.1755        | 49.0  | 686  | 0.1439          | 0.9524   | 0.0002 |
| 0.2242        | 50.0  | 700  | 0.1324          | 0.9524   | 0.0002 |
| 0.2211        | 51.0  | 714  | 0.1277          | 0.9524   | 0.0001 |
| 0.1589        | 52.0  | 728  | 0.1268          | 0.9405   | 0.0001 |
| 0.2339        | 53.0  | 742  | 0.1248          | 0.9524   | 0.0001 |
| 0.1963        | 54.0  | 756  | 0.1332          | 0.9524   | 0.0001 |
| 0.2195        | 55.0  | 770  | 0.1350          | 0.9524   | 0.0001 |
| 0.1619        | 56.0  | 784  | 0.1246          | 0.9524   | 0.0001 |
| 0.2054        | 57.0  | 798  | 0.1282          | 0.9524   | 5e-05  |
| 0.206         | 58.0  | 812  | 0.1243          | 0.9524   | 0.0000 |
| 0.188         | 59.0  | 826  | 0.1260          | 0.9524   | 0.0000 |
| 0.1891        | 60.0  | 840  | 0.1260          | 0.9524   | 0.0    |


### Framework versions

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