readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: token_fine_tunned_flipkart_2
    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. -->
  
  # token_fine_tunned_flipkart_2
  
  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: 0.3435
  - Precision: 0.8797
  - Recall: 0.9039
  - F1: 0.8916
  - Accuracy: 0.9061
  
  ## 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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 109  | 0.5647          | 0.7398    | 0.8123 | 0.7744 | 0.8111   |
  | No log        | 2.0   | 218  | 0.3863          | 0.8165    | 0.8751 | 0.8448 | 0.8716   |
  | No log        | 3.0   | 327  | 0.3367          | 0.8599    | 0.8847 | 0.8721 | 0.8869   |
  | No log        | 4.0   | 436  | 0.3266          | 0.8688    | 0.8911 | 0.8798 | 0.8977   |
  | 0.527         | 5.0   | 545  | 0.3508          | 0.8595    | 0.8898 | 0.8744 | 0.8909   |
  | 0.527         | 6.0   | 654  | 0.3410          | 0.8748    | 0.9045 | 0.8894 | 0.9009   |
  | 0.527         | 7.0   | 763  | 0.3431          | 0.8754    | 0.9045 | 0.8897 | 0.9049   |
  | 0.527         | 8.0   | 872  | 0.3435          | 0.8797    | 0.9039 | 0.8916 | 0.9061   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  