readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: token_fine_tunned_flipkart_2_gl6
    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_gl6
  
  This model is a fine-tuned version of [vinayak361/token_fine_tunned_flipkart_2_gl](https://huggingface.co/vinayak361/token_fine_tunned_flipkart_2_gl) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7363
  - Precision: 0.7243
  - Recall: 0.7752
  - F1: 0.7489
  - Accuracy: 0.7558
  
  ## 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-06
  - 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 120  | 1.0057          | 0.6623    | 0.7212 | 0.6905 | 0.6995   |
  | No log        | 2.0   | 240  | 0.8581          | 0.6660    | 0.7290 | 0.6961 | 0.7080   |
  | No log        | 3.0   | 360  | 0.8085          | 0.6882    | 0.7518 | 0.7186 | 0.7302   |
  | No log        | 4.0   | 480  | 0.7890          | 0.6970    | 0.7575 | 0.7260 | 0.7332   |
  | 0.92          | 5.0   | 600  | 0.7716          | 0.7036    | 0.7596 | 0.7305 | 0.7372   |
  | 0.92          | 6.0   | 720  | 0.7573          | 0.7028    | 0.7603 | 0.7304 | 0.7397   |
  | 0.92          | 7.0   | 840  | 0.7510          | 0.7135    | 0.7653 | 0.7385 | 0.7462   |
  | 0.92          | 8.0   | 960  | 0.7509          | 0.7192    | 0.7688 | 0.7432 | 0.7472   |
  | 0.7004        | 9.0   | 1080 | 0.7409          | 0.7181    | 0.7717 | 0.7439 | 0.7472   |
  | 0.7004        | 10.0  | 1200 | 0.7428          | 0.7155    | 0.7710 | 0.7422 | 0.7492   |
  | 0.7004        | 11.0  | 1320 | 0.7414          | 0.7223    | 0.7752 | 0.7479 | 0.7523   |
  | 0.7004        | 12.0  | 1440 | 0.7426          | 0.7207    | 0.7710 | 0.7450 | 0.7492   |
  | 0.6265        | 13.0  | 1560 | 0.7368          | 0.7255    | 0.7745 | 0.7492 | 0.7553   |
  | 0.6265        | 14.0  | 1680 | 0.7388          | 0.7239    | 0.7738 | 0.7480 | 0.7538   |
  | 0.6265        | 15.0  | 1800 | 0.7338          | 0.7239    | 0.7738 | 0.7480 | 0.7538   |
  | 0.6265        | 16.0  | 1920 | 0.7368          | 0.7243    | 0.7752 | 0.7489 | 0.7548   |
  | 0.5879        | 17.0  | 2040 | 0.7371          | 0.7270    | 0.7767 | 0.7510 | 0.7568   |
  | 0.5879        | 18.0  | 2160 | 0.7371          | 0.7243    | 0.7752 | 0.7489 | 0.7558   |
  | 0.5879        | 19.0  | 2280 | 0.7356          | 0.7247    | 0.7752 | 0.7491 | 0.7553   |
  | 0.5879        | 20.0  | 2400 | 0.7363          | 0.7243    | 0.7752 | 0.7489 | 0.7558   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  