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distilbert_sa_GLUE_Experiment_data_aug_stsb
This model is a fine-tuned version of distilbert-base-uncased on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 2.9982
- Pearson: 0.2057
- Spearmanr: 0.2115
- Combined Score: 0.2086
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: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 0.7165 | 1.0 | 1259 | 2.9982 | 0.2057 | 0.2115 | 0.2086 |
| 0.1449 | 2.0 | 2518 | 3.4353 | 0.1748 | 0.1797 | 0.1773 |
| 0.0735 | 3.0 | 3777 | 3.0788 | 0.1911 | 0.1920 | 0.1915 |
| 0.0475 | 4.0 | 5036 | 3.2439 | 0.1597 | 0.1573 | 0.1585 |
| 0.0349 | 5.0 | 6295 | 3.3386 | 0.1631 | 0.1676 | 0.1654 |
| 0.0298 | 6.0 | 7554 | 3.3579 | 0.1710 | 0.1787 | 0.1748 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
