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AntoineD
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camembert_classification_tools

Text Classification
Transformers
PyTorch
camembert
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +36 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.0708
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- - Accuracy: 0.175
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 48
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- - eval_batch_size: 48
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 3 | 2.0707 | 0.175 |
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- | No log | 2.0 | 6 | 2.0712 | 0.175 |
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- | No log | 3.0 | 9 | 2.0708 | 0.175 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5829
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+ - Accuracy: 0.85
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 24
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+ - eval_batch_size: 192
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 5 | 2.0695 | 0.225 |
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+ | No log | 2.0 | 10 | 1.9801 | 0.35 |
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+ | No log | 3.0 | 15 | 1.8056 | 0.425 |
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+ | No log | 4.0 | 20 | 1.5897 | 0.7 |
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+ | No log | 5.0 | 25 | 1.4156 | 0.75 |
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+ | No log | 6.0 | 30 | 1.2836 | 0.7 |
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+ | No log | 7.0 | 35 | 1.1515 | 0.775 |
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+ | No log | 8.0 | 40 | 1.0282 | 0.775 |
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+ | No log | 9.0 | 45 | 0.9576 | 0.775 |
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+ | No log | 10.0 | 50 | 0.9092 | 0.775 |
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+ | No log | 11.0 | 55 | 0.8485 | 0.775 |
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+ | No log | 12.0 | 60 | 0.8174 | 0.8 |
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+ | No log | 13.0 | 65 | 0.7209 | 0.85 |
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+ | No log | 14.0 | 70 | 0.6694 | 0.825 |
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+ | No log | 15.0 | 75 | 0.6861 | 0.85 |
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+ | No log | 16.0 | 80 | 0.6568 | 0.85 |
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+ | No log | 17.0 | 85 | 0.6391 | 0.85 |
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+ | No log | 18.0 | 90 | 0.6134 | 0.825 |
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+ | No log | 19.0 | 95 | 0.6149 | 0.8 |
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+ | No log | 20.0 | 100 | 0.6222 | 0.825 |
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+ | No log | 21.0 | 105 | 0.6155 | 0.825 |
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+ | No log | 22.0 | 110 | 0.5882 | 0.825 |
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+ | No log | 23.0 | 115 | 0.5737 | 0.85 |
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+ | No log | 24.0 | 120 | 0.5858 | 0.85 |
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+ | No log | 25.0 | 125 | 0.5933 | 0.825 |
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+ | No log | 26.0 | 130 | 0.5870 | 0.85 |
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+ | No log | 27.0 | 135 | 0.5859 | 0.85 |
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+ | No log | 28.0 | 140 | 0.5840 | 0.85 |
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+ | No log | 29.0 | 145 | 0.5832 | 0.85 |
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+ | No log | 30.0 | 150 | 0.5829 | 0.85 |
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  ### Framework versions
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