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End of training

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README.md CHANGED
@@ -1,7 +1,6 @@
1
  ---
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  library_name: transformers
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- license: apache-2.0
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- base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -17,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-practice-classifier
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5419
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- - Accuracy: 0.524
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- - Auc: 0.65
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- - Precision: 0.714
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  ## Model description
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@@ -42,8 +41,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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- - train_batch_size: 5
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- - eval_batch_size: 5
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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
@@ -53,21 +52,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|
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- | 0.5815 | 1.0 | 34 | 0.6348 | 0.619 | 0.688 | 0.9 |
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- | 0.5744 | 2.0 | 68 | 0.5624 | 0.667 | 0.688 | 0.765 |
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- | 0.5532 | 3.0 | 102 | 0.5057 | 0.762 | 0.688 | 0.789 |
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- | 0.563 | 4.0 | 136 | 0.5677 | 0.571 | 0.688 | 0.769 |
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- | 0.514 | 5.0 | 170 | 0.5423 | 0.667 | 0.662 | 0.765 |
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- | 0.5349 | 6.0 | 204 | 0.5564 | 0.571 | 0.65 | 0.769 |
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- | 0.5298 | 7.0 | 238 | 0.5672 | 0.571 | 0.65 | 0.769 |
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- | 0.4964 | 8.0 | 272 | 0.5173 | 0.667 | 0.65 | 0.765 |
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- | 0.5083 | 9.0 | 306 | 0.5435 | 0.571 | 0.65 | 0.769 |
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- | 0.4908 | 10.0 | 340 | 0.5419 | 0.524 | 0.65 | 0.714 |
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  ### Framework versions
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- - Transformers 4.48.3
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- - Pytorch 2.5.1+cu124
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- - Datasets 3.3.2
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- - Tokenizers 0.21.0
 
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  ---
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  library_name: transformers
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+ base_model: microsoft/codebert-base
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
16
 
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  # bert-practice-classifier
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+ This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1945
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+ - Accuracy: 0.981
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+ - Auc: 0.998
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+ - Precision: 0.944
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  ## Model description
27
 
 
41
 
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  The following hyperparameters were used during training:
43
  - learning_rate: 0.0002
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|
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+ | 0.6508 | 1.0 | 26 | 0.4846 | 0.83 | 0.966 | 1.0 |
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+ | 0.5433 | 2.0 | 52 | 0.4160 | 0.717 | 0.975 | 1.0 |
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+ | 0.5118 | 3.0 | 78 | 0.3608 | 0.925 | 0.993 | 0.81 |
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+ | 0.4396 | 4.0 | 104 | 0.3048 | 0.981 | 0.997 | 1.0 |
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+ | 0.3796 | 5.0 | 130 | 0.2879 | 0.906 | 0.998 | 1.0 |
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+ | 0.3277 | 6.0 | 156 | 0.2418 | 0.962 | 0.998 | 0.895 |
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+ | 0.3202 | 7.0 | 182 | 0.2406 | 0.962 | 0.998 | 1.0 |
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+ | 0.278 | 8.0 | 208 | 0.2087 | 0.962 | 0.998 | 0.895 |
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+ | 0.2823 | 9.0 | 234 | 0.1968 | 0.962 | 0.998 | 0.941 |
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+ | 0.2718 | 10.0 | 260 | 0.1945 | 0.981 | 0.998 | 0.944 |
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  ### Framework versions
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+ - Transformers 4.50.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.1
config.json CHANGED
@@ -1,33 +1,36 @@
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