miny-bert-aug-sst2-distilled
This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 on the augmented_glue_sst2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2643
- Accuracy: 0.9128
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: 6e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 |
---|---|---|---|---|
0.602 | 1.0 | 6227 | 0.3389 | 0.9186 |
0.4195 | 2.0 | 12454 | 0.2989 | 0.9151 |
0.3644 | 3.0 | 18681 | 0.2794 | 0.9117 |
0.3304 | 4.0 | 24908 | 0.2793 | 0.9106 |
0.3066 | 5.0 | 31135 | 0.2659 | 0.9186 |
0.2881 | 6.0 | 37362 | 0.2668 | 0.9140 |
0.2754 | 7.0 | 43589 | 0.2643 | 0.9128 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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