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AntoineD
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camembert_classification_tools_qlora

Text Classification
Transformers
PyTorch
camembert
Generated from Trainer
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  1. README.md +52 -4
README.md CHANGED
@@ -17,7 +17,7 @@ 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: 2.0567
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  - Accuracy: 0.2941
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  ## Model description
@@ -43,14 +43,62 @@ The following hyperparameters were used during training:
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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: 2
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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 | 4 | 2.0607 | 0.2941 |
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- | No log | 2.0 | 8 | 2.0567 | 0.2941 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 1.8996
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  - Accuracy: 0.2941
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  ## Model description
 
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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: 50
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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 | 4 | 2.0661 | 0.2157 |
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+ | No log | 2.0 | 8 | 2.0535 | 0.2745 |
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+ | No log | 3.0 | 12 | 2.0413 | 0.2941 |
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+ | No log | 4.0 | 16 | 2.0300 | 0.2941 |
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+ | No log | 5.0 | 20 | 2.0194 | 0.2941 |
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+ | No log | 6.0 | 24 | 2.0096 | 0.2941 |
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+ | No log | 7.0 | 28 | 2.0004 | 0.2941 |
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+ | No log | 8.0 | 32 | 1.9918 | 0.2941 |
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+ | No log | 9.0 | 36 | 1.9840 | 0.2941 |
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+ | No log | 10.0 | 40 | 1.9767 | 0.2941 |
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+ | No log | 11.0 | 44 | 1.9697 | 0.2941 |
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+ | No log | 12.0 | 48 | 1.9631 | 0.2941 |
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+ | No log | 13.0 | 52 | 1.9573 | 0.2941 |
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+ | No log | 14.0 | 56 | 1.9519 | 0.2941 |
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+ | No log | 15.0 | 60 | 1.9472 | 0.2941 |
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+ | No log | 16.0 | 64 | 1.9428 | 0.2941 |
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+ | No log | 17.0 | 68 | 1.9388 | 0.2941 |
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+ | No log | 18.0 | 72 | 1.9353 | 0.2941 |
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+ | No log | 19.0 | 76 | 1.9320 | 0.2941 |
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+ | No log | 20.0 | 80 | 1.9292 | 0.2941 |
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+ | No log | 21.0 | 84 | 1.9267 | 0.2941 |
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+ | No log | 22.0 | 88 | 1.9242 | 0.2941 |
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+ | No log | 23.0 | 92 | 1.9220 | 0.2941 |
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+ | No log | 24.0 | 96 | 1.9199 | 0.2941 |
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+ | No log | 25.0 | 100 | 1.9179 | 0.2941 |
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+ | No log | 26.0 | 104 | 1.9162 | 0.2941 |
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+ | No log | 27.0 | 108 | 1.9144 | 0.2941 |
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+ | No log | 28.0 | 112 | 1.9128 | 0.2941 |
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+ | No log | 29.0 | 116 | 1.9114 | 0.2941 |
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+ | No log | 30.0 | 120 | 1.9101 | 0.2941 |
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+ | No log | 31.0 | 124 | 1.9090 | 0.2941 |
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+ | No log | 32.0 | 128 | 1.9079 | 0.2941 |
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+ | No log | 33.0 | 132 | 1.9069 | 0.2941 |
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+ | No log | 34.0 | 136 | 1.9059 | 0.2941 |
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+ | No log | 35.0 | 140 | 1.9050 | 0.2941 |
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+ | No log | 36.0 | 144 | 1.9042 | 0.2941 |
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+ | No log | 37.0 | 148 | 1.9035 | 0.2941 |
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+ | No log | 38.0 | 152 | 1.9029 | 0.2941 |
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+ | No log | 39.0 | 156 | 1.9023 | 0.2941 |
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+ | No log | 40.0 | 160 | 1.9018 | 0.2941 |
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+ | No log | 41.0 | 164 | 1.9014 | 0.2941 |
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+ | No log | 42.0 | 168 | 1.9010 | 0.2941 |
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+ | No log | 43.0 | 172 | 1.9006 | 0.2941 |
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+ | No log | 44.0 | 176 | 1.9004 | 0.2941 |
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+ | No log | 45.0 | 180 | 1.9001 | 0.2941 |
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+ | No log | 46.0 | 184 | 1.9000 | 0.2941 |
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+ | No log | 47.0 | 188 | 1.8998 | 0.2941 |
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+ | No log | 48.0 | 192 | 1.8997 | 0.2941 |
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+ | No log | 49.0 | 196 | 1.8996 | 0.2941 |
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+ | No log | 50.0 | 200 | 1.8996 | 0.2941 |
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  ### Framework versions