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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: 0.1041 |
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- Micro f1: 0.6590 |
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- Macro f1: 0.0721 |
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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 | 0.2840 | 0.3791 | 0.0172 | |
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| No log | 2.0 | 98 | 0.1717 | 0.3791 | 0.0172 | |
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| No log | 3.0 | 147 | 0.1436 | 0.3796 | 0.0173 | |
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| No log | 4.0 | 196 | 0.1335 | 0.4608 | 0.0299 | |
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| No log | 5.0 | 245 | 0.1250 | 0.5254 | 0.0371 | |
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| No log | 6.0 | 294 | 0.1179 | 0.6312 | 0.0674 | |
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| No log | 7.0 | 343 | 0.1125 | 0.6097 | 0.0549 | |
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| No log | 8.0 | 392 | 0.1089 | 0.6368 | 0.0659 | |
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| No log | 9.0 | 441 | 0.1061 | 0.6562 | 0.0715 | |
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| No log | 10.0 | 490 | 0.1055 | 0.6525 | 0.0706 | |
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| 0.1604 | 11.0 | 539 | 0.1030 | 0.6636 | 0.0723 | |
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| 0.1604 | 12.0 | 588 | 0.1043 | 0.6526 | 0.0708 | |
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| 0.1604 | 13.0 | 637 | 0.1039 | 0.6561 | 0.0709 | |
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| 0.1604 | 14.0 | 686 | 0.1050 | 0.6576 | 0.0712 | |
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| 0.1604 | 15.0 | 735 | 0.1060 | 0.6530 | 0.0749 | |
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| 0.1604 | 16.0 | 784 | 0.1056 | 0.6606 | 0.0827 | |
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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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