readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  - precision
  - recall
  model-index:
  - name: finetuned-sentiment-analysis-model
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: imdb
        type: imdb
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.909
      - name: Precision
        type: precision
        value: 0.8899803536345776
      - name: Recall
        type: recall
        value: 0.9282786885245902
  ---
  
  <!-- 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. -->
  
  # finetuned-sentiment-analysis-model
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2868
  - Accuracy: 0.909
  - Precision: 0.8900
  - Recall: 0.9283
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  