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---
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
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