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---
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: 0.1077
- Micro f1: 0.6520
- Macro f1: 0.0704
## 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 | 0.2835 | 0.3791 | 0.0172 |
| No log | 2.0 | 98 | 0.1710 | 0.3791 | 0.0172 |
| No log | 3.0 | 147 | 0.1433 | 0.3791 | 0.0172 |
| No log | 4.0 | 196 | 0.1333 | 0.4540 | 0.0291 |
| No log | 5.0 | 245 | 0.1247 | 0.5206 | 0.0352 |
| No log | 6.0 | 294 | 0.1173 | 0.6003 | 0.0541 |
| No log | 7.0 | 343 | 0.1125 | 0.6315 | 0.0671 |
| No log | 8.0 | 392 | 0.1095 | 0.6439 | 0.0699 |
| No log | 9.0 | 441 | 0.1072 | 0.6531 | 0.0713 |
| No log | 10.0 | 490 | 0.1075 | 0.6397 | 0.0695 |
| 0.1605 | 11.0 | 539 | 0.1074 | 0.6591 | 0.0711 |
| 0.1605 | 12.0 | 588 | 0.1043 | 0.6462 | 0.0703 |
| 0.1605 | 13.0 | 637 | 0.1049 | 0.6541 | 0.0709 |
| 0.1605 | 14.0 | 686 | 0.1051 | 0.6524 | 0.0713 |
| 0.1605 | 15.0 | 735 | 0.1061 | 0.6535 | 0.0770 |
| 0.1605 | 16.0 | 784 | 0.1034 | 0.6511 | 0.0708 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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