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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: token_fine_tunned_flipkart_2
    results: []

token_fine_tunned_flipkart_2

This model is a fine-tuned version of 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