distilbert-base-uncased-textclassification_lora
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2613
- Accuracy: 0.8914
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2883 | 1.0 | 1563 | 0.2718 | 0.8844 |
| 0.2742 | 2.0 | 3126 | 0.2613 | 0.8914 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Yeji-Seong/distilbert-base-uncased-textclassification_lora
Base model
distilbert/distilbert-base-uncased