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--- |
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base_model: bigcode/starcoderbase-1b |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: bigcode-starcoderbase-1b-finetuned-defect-detection |
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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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# bigcode-starcoderbase-1b-finetuned-defect-detection |
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This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5149 |
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- Accuracy: 0.7523 |
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- F1: 0.7482 |
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- Precision: 0.7430 |
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- Recall: 0.7533 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 4711 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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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 | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.7604 | 1.0 | 996 | 0.5379 | 0.7144 | 0.6627 | 0.7829 | 0.5745 | |
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| 0.4649 | 2.0 | 1992 | 0.4524 | 0.7480 | 0.7585 | 0.7129 | 0.8104 | |
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| 0.318 | 3.0 | 2988 | 0.5149 | 0.7523 | 0.7482 | 0.7430 | 0.7533 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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