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- ---
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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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-
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- # Model Description
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-
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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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-
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- It achieves the following results on the evaluation set:
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- - Accuracy: 0.7862
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-
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- ### Training hyperparameters
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-
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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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-
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- ### Codes
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- https://github.com/IvanLauLinTiong/IntelliLabel