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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
model-index:
  - name: mobilebert_add_GLUE_Experiment_logit_kd_sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE SST2
          type: glue
          config: sst2
          split: validation
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.801605504587156

mobilebert_add_GLUE_Experiment_logit_kd_sst2

This model is a fine-tuned version of google/mobilebert-uncased on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7778
  • Accuracy: 0.8016

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
1.5405 1.0 527 1.4225 0.5539
1.3567 2.0 1054 1.4707 0.5482
1.2859 3.0 1581 1.4661 0.5677
1.2563 4.0 2108 1.4136 0.5665
1.2414 5.0 2635 1.4239 0.5940
1.2288 6.0 3162 1.4443 0.5745
0.7679 7.0 3689 0.7870 0.7878
0.4135 8.0 4216 0.7778 0.8016
0.3376 9.0 4743 0.8673 0.7993
0.2972 10.0 5270 0.8790 0.7901
0.2734 11.0 5797 0.9525 0.7913
0.2569 12.0 6324 0.9557 0.7936
0.2431 13.0 6851 0.9595 0.7878

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.9.0
  • Tokenizers 0.13.2