readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: token_fine_tunned_flipkart_2_gl
    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_gl
  
  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: 0.0275
  - Precision: 0.9888
  - Recall: 0.9900
  - F1: 0.9894
  - Accuracy: 0.9924
  
  ## 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   | 136  | 0.1945          | 0.9023    | 0.9338 | 0.9178 | 0.9331   |
  | No log        | 2.0   | 272  | 0.1232          | 0.9469    | 0.9572 | 0.9520 | 0.9658   |
  | No log        | 3.0   | 408  | 0.0852          | 0.9595    | 0.9688 | 0.9641 | 0.9747   |
  | 0.2214        | 4.0   | 544  | 0.0603          | 0.9723    | 0.9760 | 0.9741 | 0.9831   |
  | 0.2214        | 5.0   | 680  | 0.0455          | 0.9770    | 0.9819 | 0.9794 | 0.9865   |
  | 0.2214        | 6.0   | 816  | 0.0357          | 0.9823    | 0.9863 | 0.9843 | 0.9887   |
  | 0.2214        | 7.0   | 952  | 0.0307          | 0.9869    | 0.9894 | 0.9882 | 0.9916   |
  | 0.0938        | 8.0   | 1088 | 0.0275          | 0.9888    | 0.9900 | 0.9894 | 0.9924   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  