readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: model_broadclass_onSet3
    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. -->
  
  # model_broadclass_onSet3
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.1389
  - eval_0_precision: 1.0
  - eval_0_recall: 1.0
  - eval_0_f1-score: 1.0
  - eval_0_support: 23
  - eval_1_precision: 0.9697
  - eval_1_recall: 0.9697
  - eval_1_f1-score: 0.9697
  - eval_1_support: 33
  - eval_2_precision: 1.0
  - eval_2_recall: 1.0
  - eval_2_f1-score: 1.0
  - eval_2_support: 26
  - eval_3_precision: 0.9333
  - eval_3_recall: 0.9333
  - eval_3_f1-score: 0.9333
  - eval_3_support: 15
  - eval_accuracy: 0.9794
  - eval_macro avg_precision: 0.9758
  - eval_macro avg_recall: 0.9758
  - eval_macro avg_f1-score: 0.9758
  - eval_macro avg_support: 97
  - eval_weighted avg_precision: 0.9794
  - eval_weighted avg_recall: 0.9794
  - eval_weighted avg_f1-score: 0.9794
  - eval_weighted avg_support: 97
  - eval_wer: 0.1037
  - eval_mtrix: [[0, 1, 2, 3], [0, 23, 0, 0, 0], [1, 0, 32, 0, 1], [2, 0, 0, 26, 0], [3, 0, 1, 0, 14]]
  - eval_runtime: 5.6481
  - eval_samples_per_second: 17.174
  - eval_steps_per_second: 2.302
  - step: 0
  
  ## 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: 0.0003
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 80
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  