distilbert_add_GLUE_Experiment_logit_kd_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: 1.1348
- 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 |
|---|---|---|---|---|---|---|
| 3.4305 | 1.0 | 23 | 2.1402 | -0.0344 | -0.0359 | -0.0352 |
| 2.3785 | 2.0 | 46 | 1.6911 | nan | nan | nan |
| 1.8497 | 3.0 | 69 | 1.3624 | -0.0028 | -0.0046 | -0.0037 |
| 1.455 | 4.0 | 92 | 1.1653 | nan | nan | nan |
| 1.1878 | 5.0 | 115 | 1.1348 | nan | nan | nan |
| 1.0926 | 6.0 | 138 | 1.1581 | nan | nan | nan |
| 1.0833 | 7.0 | 161 | 1.1832 | nan | nan | nan |
| 1.0904 | 8.0 | 184 | 1.2266 | 0.0782 | 0.0759 | 0.0771 |
| 1.0833 | 9.0 | 207 | 1.1724 | 0.0826 | 0.0744 | 0.0785 |
| 1.0805 | 10.0 | 230 | 1.1530 | 0.0798 | 0.0761 | 0.0779 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2