readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-amazon-shoe-reviews
    results: []
  ---
  
  # distilbert-amazon-shoe-reviews
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on a [subset](https://huggingface.co/datasets/juliensimon/amazon-shoe-reviews) of the [Amazon US reviews](https://huggingface.co/datasets/amazon_us_reviews) dataset.
  
  It achieves the following results on the evaluation set:
  - Loss: 0.9532
  - Accuracy: 0.5779
  - F1: [0.62616119 0.46456105 0.50993865 0.55755123 0.734375  ]
  - Precision: [0.62757927 0.46676662 0.49148534 0.58430541 0.72415507]
  - Recall: [0.6247495  0.46237624 0.52983172 0.53313982 0.74488753]
  
  ## 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                                                   |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
  | 0.9713        | 1.0   | 2813 | 0.9532          | 0.5779   | [0.62616119 0.46456105 0.50993865 0.55755123 0.734375  ] | [0.62757927 0.46676662 0.49148534 0.58430541 0.72415507] | [0.6247495  0.46237624 0.52983172 0.53313982 0.74488753] |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  