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End of training

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  1. README.md +31 -11
  2. model.safetensors +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ 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: 0.2378
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- - Precision: 0.7015
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- - Recall: 0.6115
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- - F1: 0.6534
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- - Accuracy: 0.9182
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  ## Model description
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@@ -50,17 +50,37 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH 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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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 24 | 0.3755 | 0.0 | 0.0 | 0.0 | 0.8739 |
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- | No log | 2.0 | 48 | 0.3258 | 0.0 | 0.0 | 0.0 | 0.8739 |
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- | No log | 3.0 | 72 | 0.2695 | 0.0 | 0.0 | 0.0 | 0.8739 |
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- | No log | 4.0 | 96 | 0.2439 | 0.6749 | 0.6059 | 0.6386 | 0.9135 |
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- | No log | 5.0 | 120 | 0.2378 | 0.7015 | 0.6115 | 0.6534 | 0.9182 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.1642
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+ - Precision: 0.8721
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+ - Recall: 0.7732
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+ - F1: 0.8197
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+ - Accuracy: 0.9571
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH 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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+ - num_epochs: 25
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 24 | 0.3640 | 0.0 | 0.0 | 0.0 | 0.8739 |
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+ | No log | 2.0 | 48 | 0.2640 | 0.6884 | 0.4312 | 0.5303 | 0.9037 |
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+ | No log | 3.0 | 72 | 0.2248 | 0.6976 | 0.6431 | 0.6692 | 0.9198 |
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+ | No log | 4.0 | 96 | 0.2163 | 0.8182 | 0.6022 | 0.6938 | 0.9330 |
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+ | No log | 5.0 | 120 | 0.1690 | 0.7336 | 0.8086 | 0.7692 | 0.9388 |
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+ | No log | 6.0 | 144 | 0.1768 | 0.8558 | 0.6840 | 0.7603 | 0.9456 |
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+ | No log | 7.0 | 168 | 0.1838 | 0.8578 | 0.6952 | 0.7680 | 0.9470 |
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+ | No log | 8.0 | 192 | 0.1591 | 0.8158 | 0.8067 | 0.8112 | 0.9526 |
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+ | No log | 9.0 | 216 | 0.1688 | 0.8571 | 0.7584 | 0.8047 | 0.9536 |
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+ | No log | 10.0 | 240 | 0.1596 | 0.8431 | 0.7993 | 0.8206 | 0.9559 |
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+ | No log | 11.0 | 264 | 0.1599 | 0.8563 | 0.7751 | 0.8137 | 0.9552 |
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+ | No log | 12.0 | 288 | 0.1713 | 0.8515 | 0.7565 | 0.8012 | 0.9526 |
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+ | No log | 13.0 | 312 | 0.1646 | 0.8394 | 0.7770 | 0.8069 | 0.9531 |
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+ | No log | 14.0 | 336 | 0.1705 | 0.8367 | 0.7807 | 0.8077 | 0.9531 |
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+ | No log | 15.0 | 360 | 0.1717 | 0.8236 | 0.7900 | 0.8065 | 0.9522 |
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+ | No log | 16.0 | 384 | 0.1689 | 0.8631 | 0.7732 | 0.8157 | 0.9559 |
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+ | No log | 17.0 | 408 | 0.1608 | 0.8835 | 0.7751 | 0.8257 | 0.9587 |
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+ | No log | 18.0 | 432 | 0.1499 | 0.8849 | 0.7862 | 0.8327 | 0.9602 |
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+ | No log | 19.0 | 456 | 0.1614 | 0.8846 | 0.7695 | 0.8231 | 0.9583 |
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+ | No log | 20.0 | 480 | 0.1688 | 0.8448 | 0.7788 | 0.8104 | 0.9541 |
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+ | 0.0983 | 21.0 | 504 | 0.1672 | 0.8482 | 0.7788 | 0.8120 | 0.9545 |
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+ | 0.0983 | 22.0 | 528 | 0.1668 | 0.8563 | 0.7751 | 0.8137 | 0.9552 |
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+ | 0.0983 | 23.0 | 552 | 0.1678 | 0.8545 | 0.7751 | 0.8129 | 0.9550 |
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+ | 0.0983 | 24.0 | 576 | 0.1645 | 0.8703 | 0.7732 | 0.8189 | 0.9569 |
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+ | 0.0983 | 25.0 | 600 | 0.1642 | 0.8721 | 0.7732 | 0.8197 | 0.9571 |
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  ### Framework versions
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