distilbert_add_GLUE_Experiment_stsb_256
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: 2.2898
- Pearson: 0.0723
- Spearmanr: 0.0744
- Combined Score: 0.0733
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 |
|---|---|---|---|---|---|---|
| 5.798 | 1.0 | 23 | 3.1859 | nan | nan | nan |
| 3.2592 | 2.0 | 46 | 2.3672 | nan | nan | nan |
| 2.3588 | 3.0 | 69 | 2.3366 | nan | nan | nan |
| 2.1815 | 4.0 | 92 | 2.3354 | nan | nan | nan |
| 2.1676 | 5.0 | 115 | 2.3685 | 0.0701 | 0.0628 | 0.0665 |
| 2.1604 | 6.0 | 138 | 2.3425 | 0.0799 | 0.0728 | 0.0764 |
| 2.1203 | 7.0 | 161 | 2.2898 | 0.0723 | 0.0744 | 0.0733 |
| 1.8844 | 8.0 | 184 | 2.7739 | 0.0606 | 0.0839 | 0.0723 |
| 1.7797 | 9.0 | 207 | 2.6237 | 0.0817 | 0.0949 | 0.0883 |
| 1.7003 | 10.0 | 230 | 2.7269 | 0.0957 | 0.1082 | 0.1020 |
| 1.5943 | 11.0 | 253 | 2.6580 | 0.1212 | 0.1276 | 0.1244 |
| 1.5603 | 12.0 | 276 | 2.5384 | 0.1412 | 0.1422 | 0.1417 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2