distilbert-base-uncased-finetuned-cola-3
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0002
- Matthews Correlation: 1.0
Label 0 : "AIMX" Label 1 : "OWNX" Label 2 : "CONT" Label 3 : "BASE" Label 4 : "MISC"
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| No log | 1.0 | 192 | 0.0060 | 1.0 |
| No log | 2.0 | 384 | 0.0019 | 1.0 |
| 0.0826 | 3.0 | 576 | 0.0010 | 1.0 |
| 0.0826 | 4.0 | 768 | 0.0006 | 1.0 |
| 0.0826 | 5.0 | 960 | 0.0005 | 1.0 |
| 0.001 | 6.0 | 1152 | 0.0004 | 1.0 |
| 0.001 | 7.0 | 1344 | 0.0003 | 1.0 |
| 0.0005 | 8.0 | 1536 | 0.0003 | 1.0 |
| 0.0005 | 9.0 | 1728 | 0.0002 | 1.0 |
| 0.0005 | 10.0 | 1920 | 0.0002 | 1.0 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3