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End of training
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metadata
language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: mobilebert_add_GLUE_Experiment_qqp_128
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          config: qqp
          split: validation
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7568142468464012
          - name: F1
            type: f1
            value: 0.6361483235881874

mobilebert_add_GLUE_Experiment_qqp_128

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

  • Loss: 0.5071
  • Accuracy: 0.7568
  • F1: 0.6361
  • Combined Score: 0.6965

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: 128
  • eval_batch_size: 128
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Combined Score
0.6507 1.0 2843 0.6497 0.6318 0.0 0.3159
0.6311 2.0 5686 0.5445 0.7259 0.5622 0.6441
0.5153 3.0 8529 0.5153 0.7493 0.5892 0.6693
0.4912 4.0 11372 0.5071 0.7568 0.6361 0.6965
0.4805 5.0 14215 nan 0.6318 0.0 0.3159
0.0 6.0 17058 nan 0.6318 0.0 0.3159
0.0 7.0 19901 nan 0.6318 0.0 0.3159
0.0 8.0 22744 nan 0.6318 0.0 0.3159
0.0 9.0 25587 nan 0.6318 0.0 0.3159

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.8.0
  • Tokenizers 0.13.2