readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-distilled-model-flip_mind_epoch12_alpha0.8
    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. -->
  
  # bert-distilled-model-flip_mind_epoch12_alpha0.8
  
  This model is a fine-tuned version of [ArafatBHossain/distill_bert_fine_tuned_mind](https://huggingface.co/ArafatBHossain/distill_bert_fine_tuned_mind) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7953
  - Accuracy: 0.914
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.8595        | 1.0   | 3054  | 1.8311          | 0.854    |
  | 1.7769        | 2.0   | 6108  | 1.7204          | 0.847    |
  | 1.7614        | 3.0   | 9162  | 1.7666          | 0.8666   |
  | 1.7212        | 4.0   | 12216 | 1.8134          | 0.8716   |
  | 1.7255        | 5.0   | 15270 | 1.7368          | 0.8812   |
  | 1.6845        | 6.0   | 18324 | 1.7368          | 0.8898   |
  | 1.7346        | 7.0   | 21378 | 1.6621          | 0.8936   |
  | 1.7436        | 8.0   | 24432 | 1.7180          | 0.9008   |
  | 1.7333        | 9.0   | 27486 | 1.7523          | 0.9048   |
  | 1.7805        | 10.0  | 30540 | 1.7820          | 0.9078   |
  | 1.792         | 11.0  | 33594 | 1.7329          | 0.9096   |
  | 1.7463        | 12.0  | 36648 | 1.7953          | 0.914    |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.11.0
  - Datasets 2.6.1
  - Tokenizers 0.12.1
  