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BERRAMOU
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camembert-math-classification

Text Classification
Transformers
Safetensors
camembert
Generated from Trainer
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  1. README.md +12 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,13 +18,13 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3074
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- - F1 Macro: 1.0
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- - F1 Weighted: 1.0
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- - F1 Correct: 1.0
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- - F1 Partiel: 1.0
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- - F1 Incorrect: 1.0
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- - Accuracy: 1.0
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  ## Model description
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@@ -50,18 +50,17 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 0.1
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- - num_epochs: 5
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Correct | F1 Partiel | F1 Incorrect | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:----------:|:----------:|:------------:|:--------:|
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- | No log | 1.0 | 15 | 0.5744 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.7563 | 2.0 | 30 | 0.4487 | 0.9839 | 0.9834 | 1.0 | 0.9787 | 0.9730 | 0.9833 |
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- | 0.5266 | 3.0 | 45 | 0.4066 | 0.9839 | 0.9834 | 0.9730 | 0.9787 | 1.0 | 0.9833 |
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- | 0.4057 | 4.0 | 60 | 0.3360 | 0.9839 | 0.9834 | 1.0 | 0.9787 | 0.9730 | 0.9833 |
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- | 0.4057 | 5.0 | 75 | 0.3074 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6519
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+ - F1 Macro: 0.6973
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+ - F1 Weighted: 0.7076
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+ - F1 Correct: 0.8571
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+ - F1 Partiel: 0.8
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+ - F1 Incorrect: 0.4348
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+ - Accuracy: 0.75
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 0.1
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+ - num_epochs: 4
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Correct | F1 Partiel | F1 Incorrect | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:----------:|:----------:|:------------:|:--------:|
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+ | No log | 1.0 | 15 | 2.1103 | 0.1905 | 0.2286 | 0.0 | 0.5714 | 0.0 | 0.4 |
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+ | 2.1496 | 2.0 | 30 | 1.9187 | 0.2928 | 0.3228 | 0.2857 | 0.5926 | 0.0 | 0.45 |
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+ | 2.0111 | 3.0 | 45 | 1.7323 | 0.7855 | 0.7870 | 0.9412 | 0.8 | 0.6154 | 0.8 |
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+ | 1.8019 | 4.0 | 60 | 1.6519 | 0.6973 | 0.7076 | 0.8571 | 0.8 | 0.4348 | 0.75 |
 
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  ### Framework versions
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