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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_sa_GLUE_Experiment_logit_kd_mnli_256
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          config: mnli
          split: validation_matched
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6119812855980472

mobilebert_sa_GLUE_Experiment_logit_kd_mnli_256

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

  • Loss: 1.2282
  • Accuracy: 0.6120

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
1.6433 1.0 3068 1.4078 0.5457
1.4683 2.0 6136 1.3590 0.5658
1.4077 3.0 9204 1.3106 0.5772
1.3591 4.0 12272 1.2971 0.5904
1.3213 5.0 15340 1.2764 0.5957
1.2849 6.0 18408 1.2562 0.6029
1.2475 7.0 21476 1.2524 0.6038
1.2073 8.0 24544 1.2384 0.6066
1.1713 9.0 27612 1.2377 0.6109
1.1371 10.0 30680 1.2228 0.6077
1.1069 11.0 33748 1.2126 0.6196
1.0775 12.0 36816 1.2232 0.6271
1.0491 13.0 39884 1.2440 0.6110
1.0228 14.0 42952 1.2741 0.6079
0.9977 15.0 46020 1.2448 0.6158
0.974 16.0 49088 1.3261 0.6206

Framework versions

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