readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-distilled-multi_teacher_avg_logit_twitter_sentiment_07_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-multi_teacher_avg_logit_twitter_sentiment_07_alpha0.8
  
  This model is a fine-tuned version of [ArafatBHossain/distilbert-base-uncased-twitter_eval_sentiment_data](https://huggingface.co/ArafatBHossain/distilbert-base-uncased-twitter_eval_sentiment_data) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3250
  - Accuracy: 0.671
  
  ## 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: 7
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.4044        | 1.0   | 1875  | 0.3820          | 0.6655   |
  | 0.2636        | 2.0   | 3750  | 0.3914          | 0.668    |
  | 0.206         | 3.0   | 5625  | 0.3595          | 0.6655   |
  | 0.1694        | 4.0   | 7500  | 0.3548          | 0.6725   |
  | 0.1437        | 5.0   | 9375  | 0.3360          | 0.6725   |
  | 0.1272        | 6.0   | 11250 | 0.3259          | 0.6755   |
  | 0.1167        | 7.0   | 13125 | 0.3250          | 0.671    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  