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distilbert_add_GLUE_Experiment_stsb_192
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: 2.2659
- Pearson: nan
- Spearmanr: nan
- Combined Score: nan
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 |
|---|---|---|---|---|---|---|
| 7.0456 | 1.0 | 23 | 4.3280 | nan | nan | nan |
| 4.7979 | 2.0 | 46 | 3.4200 | nan | nan | nan |
| 3.7359 | 3.0 | 69 | 2.7494 | nan | nan | nan |
| 2.9308 | 4.0 | 92 | 2.3396 | nan | nan | nan |
| 2.3776 | 5.0 | 115 | 2.2659 | nan | nan | nan |
| 2.1865 | 6.0 | 138 | 2.3171 | nan | nan | nan |
| 2.1731 | 7.0 | 161 | 2.3598 | nan | nan | nan |
| 2.1793 | 8.0 | 184 | 2.4690 | 0.1389 | 0.1432 | 0.1410 |
| 2.1725 | 9.0 | 207 | 2.3589 | 0.0899 | 0.0808 | 0.0854 |
| 2.1621 | 10.0 | 230 | 2.3156 | 0.0853 | 0.0802 | 0.0827 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
