Rami/multi-label-class-classification-on-github-issues

1---2tags:3- generated_from_trainer4model-index:5- name: multi-label-class-classification-on-github-issues6  results: []7---8 9<!-- This model card has been generated automatically according to the information the Trainer had access to. You10should probably proofread and complete it, then remove this comment. -->11 12# multi-label-class-classification-on-github-issues13 14This 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.15It achieves the following results on the evaluation set:16- Loss: 0.107717- Micro f1: 0.652018- Macro f1: 0.070419 20## Model description21 22More information needed23 24## Intended uses & limitations25 26More information needed27 28## Training and evaluation data29 30More information needed31 32## Training procedure33 34### Training hyperparameters35 36The following hyperparameters were used during training:37- learning_rate: 3e-0538- train_batch_size: 6439- eval_batch_size: 840- seed: 4241- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0842- lr_scheduler_type: linear43- num_epochs: 3044- mixed_precision_training: Native AMP45 46### Training results47 48| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |49|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|50| No log        | 1.0   | 49   | 0.2835          | 0.3791   | 0.0172   |51| No log        | 2.0   | 98   | 0.1710          | 0.3791   | 0.0172   |52| No log        | 3.0   | 147  | 0.1433          | 0.3791   | 0.0172   |53| No log        | 4.0   | 196  | 0.1333          | 0.4540   | 0.0291   |54| No log        | 5.0   | 245  | 0.1247          | 0.5206   | 0.0352   |55| No log        | 6.0   | 294  | 0.1173          | 0.6003   | 0.0541   |56| No log        | 7.0   | 343  | 0.1125          | 0.6315   | 0.0671   |57| No log        | 8.0   | 392  | 0.1095          | 0.6439   | 0.0699   |58| No log        | 9.0   | 441  | 0.1072          | 0.6531   | 0.0713   |59| No log        | 10.0  | 490  | 0.1075          | 0.6397   | 0.0695   |60| 0.1605        | 11.0  | 539  | 0.1074          | 0.6591   | 0.0711   |61| 0.1605        | 12.0  | 588  | 0.1043          | 0.6462   | 0.0703   |62| 0.1605        | 13.0  | 637  | 0.1049          | 0.6541   | 0.0709   |63| 0.1605        | 14.0  | 686  | 0.1051          | 0.6524   | 0.0713   |64| 0.1605        | 15.0  | 735  | 0.1061          | 0.6535   | 0.0770   |65| 0.1605        | 16.0  | 784  | 0.1034          | 0.6511   | 0.0708   |66 67 68### Framework versions69 70- Transformers 4.25.171- Pytorch 1.13.0+cu11672- Datasets 2.8.073- Tokenizers 0.13.274