readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-amazon-shoe-reviews
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        type: amazon_us_reviews
        name: Amazon US reviews
        split: Shoes
      metrics:
      - type: accuracy
        value: 0.48
        name: Accuracy
  ---
  
  <!-- 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-amazon-shoe-reviews
  
  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: 1.3445
  - Accuracy: 0.48
  - F1: [0.         0.         0.         0.         0.64864865]
  - Precision: [0.   0.   0.   0.   0.48]
  - Recall: [0. 0. 0. 0. 1.]
  
  ## 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: 32
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1                                                       | Precision                  | Recall           |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------:|:----------------:|
  | No log        | 1.0   | 15   | 1.3445          | 0.48     | [0.         0.         0.         0.         0.64864865] | [0.   0.   0.   0.   0.48] | [0. 0. 0. 0. 1.] |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.11.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  