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distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6525
- Accuracy: 0.7580
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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 | Accuracy |
---|---|---|---|---|
0.5409 | 1.0 | 16838 | 0.6491 | 0.7569 |
0.6219 | 2.0 | 33676 | 0.6801 | 0.7557 |
0.5441 | 3.0 | 50514 | 0.6795 | 0.7259 |
0.5468 | 4.0 | 67352 | 0.6557 | 0.7305 |
0.6058 | 5.0 | 84190 | 0.6806 | 0.7156 |
0.5519 | 6.0 | 101028 | 0.6796 | 0.7225 |
0.5084 | 7.0 | 117866 | 0.7562 | 0.7259 |
0.5687 | 8.0 | 134704 | 0.6804 | 0.7317 |
0.4703 | 9.0 | 151542 | 0.6986 | 0.7282 |
0.5249 | 10.0 | 168380 | 0.6525 | 0.7580 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0