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metadata
library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/bert_tiny_olda_book_10_v1
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert_tiny_olda_book_10_v1_qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8799901063566659
          - name: F1
            type: f1
            value: 0.841251145138071

bert_tiny_olda_book_10_v1_qqp

This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_olda_book_10_v1 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2816
  • Accuracy: 0.8800
  • F1: 0.8413
  • Combined Score: 0.8606

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: 5e-05
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 10
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Combined Score
0.3941 1.0 1422 0.3365 0.8496 0.7836 0.8166
0.2912 2.0 2844 0.2905 0.8710 0.8323 0.8516
0.2365 3.0 4266 0.2816 0.8800 0.8413 0.8606
0.1917 4.0 5688 0.2965 0.8807 0.8349 0.8578
0.157 5.0 7110 0.3086 0.8831 0.8474 0.8653
0.1268 6.0 8532 0.3240 0.8849 0.8496 0.8672
0.1053 7.0 9954 0.3513 0.8878 0.8496 0.8687
0.0878 8.0 11376 0.3817 0.8864 0.8520 0.8692

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.2.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.1