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