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datasets: |
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- ticket-tagger |
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metrics: |
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- accuracy |
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model-index: |
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- name: distil-bert-uncased-finetuned-github-issues |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: ticket tagger |
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type: ticket tagger |
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args: full |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7862 |
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--- |
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# Model Description |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) and fine-tuning it on the |
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[github ticket tagger dataset](https://tickettagger.blob.core.windows.net/datasets/dataset-labels-top3-30k-real.txt). It classifies issue into 3 common categories: Bug, Enhancement, Questions. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.7862 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-5 |
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- train_batch_size: 16 |
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- optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 0 |
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- num_epochs: 5 |
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### Codes |
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https://github.com/IvanLauLinTiong/IntelliLabel |