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--- |
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library_name: peft |
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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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datasets: |
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- code_search_net |
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model-index: |
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- name: codebert-model |
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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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# codebert-model |
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This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the code_search_net dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.8346 |
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- eval_model_preparation_time: 0.0057 |
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- eval_accuracy: {'accuracy': 0.21967491508976225} |
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- eval_f1: {'f1': 0.0} |
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- eval_runtime: 9384.6382 |
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- eval_samples_per_second: 0.878 |
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- eval_steps_per_second: 0.11 |
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- step: 0 |
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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: 5e-05 |
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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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- num_epochs: 3 |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
