readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: token_fine_tunned_flipkart
    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
  
  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: 0.0992
  - Precision: 0.9526
  - Recall: 0.9669
  - F1: 0.9597
  - Accuracy: 0.9730
  
  ## 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   | 135  | 0.5967          | 0.7227    | 0.7830 | 0.7516 | 0.7932   |
  | No log        | 2.0   | 270  | 0.3673          | 0.8105    | 0.8623 | 0.8356 | 0.8747   |
  | No log        | 3.0   | 405  | 0.2679          | 0.8676    | 0.8854 | 0.8764 | 0.9094   |
  | 0.6219        | 4.0   | 540  | 0.1972          | 0.8955    | 0.9217 | 0.9084 | 0.9355   |
  | 0.6219        | 5.0   | 675  | 0.1500          | 0.9229    | 0.9374 | 0.9301 | 0.9525   |
  | 0.6219        | 6.0   | 810  | 0.1240          | 0.9341    | 0.9509 | 0.9424 | 0.9609   |
  | 0.6219        | 7.0   | 945  | 0.1041          | 0.9516    | 0.9650 | 0.9582 | 0.9720   |
  | 0.2085        | 8.0   | 1080 | 0.0992          | 0.9526    | 0.9669 | 0.9597 | 0.9730   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  