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---
base_model: camembert/camembert-base-ccnet
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_ccnet_classification_tools_qlora_fr
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_qlora_fr
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: 1.4958
- Accuracy: 0.45
## 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: 60
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 5 | 2.0916 | 0.075 |
| No log | 2.0 | 10 | 2.1165 | 0.075 |
| No log | 3.0 | 15 | 2.1285 | 0.075 |
| No log | 4.0 | 20 | 2.1210 | 0.075 |
| No log | 5.0 | 25 | 2.1182 | 0.125 |
| No log | 6.0 | 30 | 2.0984 | 0.125 |
| No log | 7.0 | 35 | 2.0764 | 0.15 |
| No log | 8.0 | 40 | 2.0390 | 0.2 |
| No log | 9.0 | 45 | 2.0085 | 0.2 |
| No log | 10.0 | 50 | 1.9749 | 0.175 |
| No log | 11.0 | 55 | 1.9474 | 0.15 |
| No log | 12.0 | 60 | 1.9271 | 0.225 |
| No log | 13.0 | 65 | 1.9089 | 0.225 |
| No log | 14.0 | 70 | 1.8945 | 0.225 |
| No log | 15.0 | 75 | 1.8847 | 0.2 |
| No log | 16.0 | 80 | 1.8638 | 0.25 |
| No log | 17.0 | 85 | 1.8387 | 0.3 |
| No log | 18.0 | 90 | 1.8156 | 0.275 |
| No log | 19.0 | 95 | 1.8003 | 0.3 |
| No log | 20.0 | 100 | 1.7827 | 0.275 |
| No log | 21.0 | 105 | 1.7688 | 0.3 |
| No log | 22.0 | 110 | 1.7467 | 0.275 |
| No log | 23.0 | 115 | 1.7255 | 0.275 |
| No log | 24.0 | 120 | 1.7132 | 0.325 |
| No log | 25.0 | 125 | 1.7007 | 0.35 |
| No log | 26.0 | 130 | 1.6881 | 0.35 |
| No log | 27.0 | 135 | 1.6801 | 0.35 |
| No log | 28.0 | 140 | 1.6642 | 0.375 |
| No log | 29.0 | 145 | 1.6450 | 0.325 |
| No log | 30.0 | 150 | 1.6425 | 0.35 |
| No log | 31.0 | 155 | 1.6305 | 0.375 |
| No log | 32.0 | 160 | 1.6193 | 0.4 |
| No log | 33.0 | 165 | 1.6128 | 0.4 |
| No log | 34.0 | 170 | 1.6027 | 0.4 |
| No log | 35.0 | 175 | 1.5915 | 0.425 |
| No log | 36.0 | 180 | 1.5837 | 0.45 |
| No log | 37.0 | 185 | 1.5721 | 0.45 |
| No log | 38.0 | 190 | 1.5605 | 0.425 |
| No log | 39.0 | 195 | 1.5555 | 0.425 |
| No log | 40.0 | 200 | 1.5521 | 0.425 |
| No log | 41.0 | 205 | 1.5480 | 0.425 |
| No log | 42.0 | 210 | 1.5399 | 0.45 |
| No log | 43.0 | 215 | 1.5276 | 0.45 |
| No log | 44.0 | 220 | 1.5282 | 0.45 |
| No log | 45.0 | 225 | 1.5197 | 0.45 |
| No log | 46.0 | 230 | 1.5175 | 0.45 |
| No log | 47.0 | 235 | 1.5065 | 0.45 |
| No log | 48.0 | 240 | 1.5043 | 0.45 |
| No log | 49.0 | 245 | 1.5019 | 0.45 |
| No log | 50.0 | 250 | 1.4975 | 0.45 |
| No log | 51.0 | 255 | 1.4949 | 0.45 |
| No log | 52.0 | 260 | 1.4969 | 0.45 |
| No log | 53.0 | 265 | 1.4958 | 0.45 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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