philschmid / bert-mini-sst2-distilled

huggingface.co
Total runs: 64
24-hour runs: -7
7-day runs: -45
30-day runs: 28
Model's Last Updated: February 01 2022
text-classification

Introduction of bert-mini-sst2-distilled

Model Details of bert-mini-sst2-distilled

bert-mini-sst2-distilled

This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 on the glue dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1792
  • Accuracy: 0.8567
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: 0.00021185586235152412
  • 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: 8
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
2.1552 1.0 66 1.4847 0.8349
0.8451 2.0 132 1.3495 0.8624
0.5864 3.0 198 1.2257 0.8532
0.4553 4.0 264 1.2571 0.8544
0.3708 5.0 330 1.2132 0.8658
0.3086 6.0 396 1.2370 0.8589
0.2701 7.0 462 1.1900 0.8635
0.246 8.0 528 1.1792 0.8567
Framework versions
  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.15.1
  • Tokenizers 0.10.3

Runs of philschmid bert-mini-sst2-distilled on huggingface.co

64
Total runs
-7
24-hour runs
-50
3-day runs
-45
7-day runs
28
30-day runs

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bert-mini-sst2-distilled install

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