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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_128
    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: 0.8073394495412844

mobilebert_add_GLUE_Experiment_logit_kd_sst2_128

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: 0.7282
  • Accuracy: 0.8073

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
1.5487 1.0 527 1.3929 0.5780
1.3629 2.0 1054 1.4979 0.5505
1.1397 3.0 1581 1.3927 0.6755
0.5649 4.0 2108 0.7289 0.8073
0.4112 5.0 2635 0.7282 0.8073
0.3462 6.0 3162 0.7654 0.8050
0.3069 7.0 3689 0.8303 0.7970
0.2833 8.0 4216 0.8806 0.7924
0.2662 9.0 4743 0.9297 0.7959
0.2521 10.0 5270 1.0979 0.7718

Framework versions

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