readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-US_Airline_Twitter_Sentiment_Analysis
    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. -->
  
  # distilbert-base-uncased-US_Airline_Twitter_Sentiment_Analysis
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5594
  - Accuracy: 0.8466
  - F1 Score: 0.8471
  
  ## 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: 2e-05
  - train_batch_size: 128
  - eval_batch_size: 128
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
  | 0.8015        | 1.0   | 92   | 0.5483          | 0.7952   | 0.8018   |
  | 0.4795        | 2.0   | 184  | 0.4993          | 0.8233   | 0.8266   |
  | 0.3995        | 3.0   | 276  | 0.5888          | 0.8205   | 0.8160   |
  | 0.339         | 4.0   | 368  | 0.4935          | 0.8349   | 0.8350   |
  | 0.2857        | 5.0   | 460  | 0.5100          | 0.8336   | 0.8370   |
  | 0.2439        | 6.0   | 552  | 0.5275          | 0.8377   | 0.8400   |
  | 0.2181        | 7.0   | 644  | 0.5463          | 0.8418   | 0.8426   |
  | 0.1983        | 8.0   | 736  | 0.5594          | 0.8466   | 0.8471   |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  