---
tags:
- generated_from_trainer
model-index:
- name: multi-label-class-classification-on-github-issues
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# multi-label-class-classification-on-github-issues

This model is a fine-tuned version of [neuralmagic/oBERT-12-upstream-pruned-unstructured-97](https://huggingface.co/neuralmagic/oBERT-12-upstream-pruned-unstructured-97) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1041
- Micro f1: 0.6590
- Macro f1: 0.0721

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   | 49   | 0.2840          | 0.3791   | 0.0172   |
| No log        | 2.0   | 98   | 0.1717          | 0.3791   | 0.0172   |
| No log        | 3.0   | 147  | 0.1436          | 0.3796   | 0.0173   |
| No log        | 4.0   | 196  | 0.1335          | 0.4608   | 0.0299   |
| No log        | 5.0   | 245  | 0.1250          | 0.5254   | 0.0371   |
| No log        | 6.0   | 294  | 0.1179          | 0.6312   | 0.0674   |
| No log        | 7.0   | 343  | 0.1125          | 0.6097   | 0.0549   |
| No log        | 8.0   | 392  | 0.1089          | 0.6368   | 0.0659   |
| No log        | 9.0   | 441  | 0.1061          | 0.6562   | 0.0715   |
| No log        | 10.0  | 490  | 0.1055          | 0.6525   | 0.0706   |
| 0.1604        | 11.0  | 539  | 0.1030          | 0.6636   | 0.0723   |
| 0.1604        | 12.0  | 588  | 0.1043          | 0.6526   | 0.0708   |
| 0.1604        | 13.0  | 637  | 0.1039          | 0.6561   | 0.0709   |
| 0.1604        | 14.0  | 686  | 0.1050          | 0.6576   | 0.0712   |
| 0.1604        | 15.0  | 735  | 0.1060          | 0.6530   | 0.0749   |
| 0.1604        | 16.0  | 784  | 0.1056          | 0.6606   | 0.0827   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2