readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ecommerce_reviews_with_language_drift
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert_reviews_with_language_drift
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: ecommerce_reviews_with_language_drift
        type: ecommerce_reviews_with_language_drift
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.818
      - name: F1
        type: f1
        value: 0.8167126877417763
  widget:
  - text: "Poor quality of fabric and ridiculously tight at chest. It's way too short."
    example_title: "Negative"
  - text: "One worked perfectly, but the other one has a slight leak and we end up with water underneath the filter."
    example_title: "Neutral"
  - text: "I liked the price most! Nothing to dislike here!"
    example_title: "Positive"
  ---
  
  <!-- 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_reviews_with_language_drift
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ecommerce_reviews_with_language_drift dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4970
  - Accuracy: 0.818
  - F1: 0.8167
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.593         | 1.0   | 500  | 0.4723          | 0.799    | 0.7976 |
  | 0.3714        | 2.0   | 1000 | 0.4679          | 0.818    | 0.8177 |
  | 0.2652        | 3.0   | 1500 | 0.4970          | 0.818    | 0.8167 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  