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README.md
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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:
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- accuracy
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model-index:
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- name: gpad-v1-entropy-taskA
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# gpad-v1-entropy-taskA
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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: 0.0423
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- Accuracy: 0.9908
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- F1 Macro: 0.9912
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- F1 Weighted: 0.9908
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- Precision Macro: 0.9921
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- Recall Macro: 0.9903
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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: 16
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- eval_batch_size: 16
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:------------:|
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| 0.0643 | 1.0 | 7813 | 0.0518 | 0.9881 | 0.9885 | 0.9881 | 0.9920 | 0.9851 |
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| 0.0261 | 2.0 | 15626 | 0.0409 | 0.9902 | 0.9906 | 0.9902 | 0.9914 | 0.9897 |
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| 0.044 | 3.0 | 23439 | 0.0423 | 0.9908 | 0.9912 | 0.9908 | 0.9921 | 0.9903 |
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### Framework versions
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- Transformers 4.53.3
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- Pytorch 2.6.0+cu124
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- Datasets 4.0.0
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- Tokenizers 0.21.2
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