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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: multi-label-class-classification-on-github-issues |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# multi-label-class-classification-on-github-issues |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1077 |
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- Micro f1: 0.6520 |
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- Macro f1: 0.0704 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| No log | 1.0 | 49 | 0.2835 | 0.3791 | 0.0172 | |
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| No log | 2.0 | 98 | 0.1710 | 0.3791 | 0.0172 | |
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| No log | 3.0 | 147 | 0.1433 | 0.3791 | 0.0172 | |
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| No log | 4.0 | 196 | 0.1333 | 0.4540 | 0.0291 | |
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| No log | 5.0 | 245 | 0.1247 | 0.5206 | 0.0352 | |
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| No log | 6.0 | 294 | 0.1173 | 0.6003 | 0.0541 | |
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| No log | 7.0 | 343 | 0.1125 | 0.6315 | 0.0671 | |
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| No log | 8.0 | 392 | 0.1095 | 0.6439 | 0.0699 | |
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| No log | 9.0 | 441 | 0.1072 | 0.6531 | 0.0713 | |
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| No log | 10.0 | 490 | 0.1075 | 0.6397 | 0.0695 | |
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| 0.1605 | 11.0 | 539 | 0.1074 | 0.6591 | 0.0711 | |
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| 0.1605 | 12.0 | 588 | 0.1043 | 0.6462 | 0.0703 | |
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| 0.1605 | 13.0 | 637 | 0.1049 | 0.6541 | 0.0709 | |
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| 0.1605 | 14.0 | 686 | 0.1051 | 0.6524 | 0.0713 | |
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| 0.1605 | 15.0 | 735 | 0.1061 | 0.6535 | 0.0770 | |
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| 0.1605 | 16.0 | 784 | 0.1034 | 0.6511 | 0.0708 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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