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distilbert_add_GLUE_Experiment_logit_kd_cola_384
This model is a fine-tuned version of distilbert-base-uncased on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6805
- Matthews Correlation: 0.1134
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 | Matthews Correlation |
|---|---|---|---|---|
| 0.8052 | 1.0 | 34 | 0.6842 | 0.0 |
| 0.7982 | 2.0 | 68 | 0.6842 | 0.0 |
| 0.7961 | 3.0 | 102 | 0.6841 | 0.0 |
| 0.7965 | 4.0 | 136 | 0.6846 | 0.0 |
| 0.799 | 5.0 | 170 | 0.6841 | 0.0 |
| 0.7956 | 6.0 | 204 | 0.6840 | 0.0 |
| 0.798 | 7.0 | 238 | 0.6860 | 0.0 |
| 0.7984 | 8.0 | 272 | 0.6839 | 0.0 |
| 0.7962 | 9.0 | 306 | 0.6875 | 0.0 |
| 0.797 | 10.0 | 340 | 0.6834 | 0.0 |
| 0.7951 | 11.0 | 374 | 0.6813 | 0.0 |
| 0.7771 | 12.0 | 408 | 0.6849 | 0.0257 |
| 0.7055 | 13.0 | 442 | 0.7093 | 0.0764 |
| 0.6664 | 14.0 | 476 | 0.6957 | 0.1007 |
| 0.654 | 15.0 | 510 | 0.6805 | 0.1134 |
| 0.6345 | 16.0 | 544 | 0.6966 | 0.1176 |
| 0.6176 | 17.0 | 578 | 0.7439 | 0.1155 |
| 0.6156 | 18.0 | 612 | 0.7178 | 0.1406 |
| 0.5938 | 19.0 | 646 | 0.7192 | 0.1212 |
| 0.582 | 20.0 | 680 | 0.7765 | 0.1506 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
