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tiny-bert-sst2-distilled

Text Classification Transformers PyTorch
bert generated_from_trainer Eval Results Inference Endpoints
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: tiny-bert-sst2-distilled
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8325688073394495

tiny-bert-sst2-distilled

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7305
  • Accuracy: 0.8326

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: 0.0007199555649276667
  • train_batch_size: 1024
  • eval_batch_size: 1024
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 7
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.77 1.0 66 1.6939 0.8165
0.729 2.0 132 1.5090 0.8326
0.5242 3.0 198 1.5369 0.8257
0.4017 4.0 264 1.7025 0.8326
0.327 5.0 330 1.6743 0.8245
0.2749 6.0 396 1.7305 0.8337
0.2521 7.0 462 1.7305 0.8326

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.15.1
  • Tokenizers 0.10.3