readme: ---
  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
  