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--- |
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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: |
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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: github_issues-dataset-distilbert-base-uncased |
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results: [] |
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datasets: |
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- lewtun/github-issues |
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language: |
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- en |
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--- |
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# github_issues-dataset-distilbert-base-uncased |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on a GitHub issues dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1495 |
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- Accuracy: 0.9580 |
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- F1: 0.6067 |
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- Precision: 0.7297 |
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- Recall: 0.5192 |
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## Model description |
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[distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) |
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## Intended uses & limitations |
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Multi Label Classification on GitHub repository issues. |
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## Training and evaluation data |
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GitHub issues dataset taken from [GitHub issues](https://huggingface.co/datasets/lewtun/github-issues). |
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Split the dataset into 80-20 train-test splits. Filtered out the pull requests and issues with no labels. |
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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: 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 | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.3962 | 1.0 | 114 | 0.2513 | 0.9208 | 0.34 | 0.3542 | 0.3269 | |
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| 0.2008 | 2.0 | 228 | 0.1847 | 0.9436 | 0.4198 | 0.5862 | 0.3269 | |
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| 0.1633 | 3.0 | 342 | 0.1608 | 0.9544 | 0.5581 | 0.7059 | 0.4615 | |
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| 0.1468 | 4.0 | 456 | 0.1519 | 0.9580 | 0.6067 | 0.7297 | 0.5192 | |
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| 0.1385 | 5.0 | 570 | 0.1495 | 0.9580 | 0.6067 | 0.7297 | 0.5192 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
