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distilbert-base-uncased-lora-text-classification
shandonk/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from shandonk. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025
- SHA
- b098d758
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 1.2612
- Accuracy: {'accuracy': 0.8287247214197276}
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6087 | 1.0 | 606 | 0.6192 | {'accuracy': 0.8018984729673958} |
| 0.4539 | 2.0 | 1212 | 0.5939 | {'accuracy': 0.8312009905076352} |
| 0.3768 | 3.0 | 1818 | 0.7302 | {'accuracy': 0.8283120099050764} |
| 0.3249 | 4.0 | 2424 | 0.7608 | {'accuracy': 0.8287247214197276} |
| 0.1923 | 5.0 | 3030 | 0.8825 | {'accuracy': 0.8283120099050764} |
| 0.1518 | 6.0 | 3636 | 1.0603 | {'accuracy': 0.8332645480808915} |
| 0.1068 | 7.0 | 4242 | 1.1702 | {'accuracy': 0.8262484523318201} |
| 0.0673 | 8.0 | 4848 | 1.2515 | {'accuracy': 0.8217086256706562} |
| 0.072 | 9.0 | 5454 | 1.2673 | {'accuracy': 0.8303755674783326} |
| 0.0315 | 10.0 | 6060 | 1.2612 | {'accuracy': 0.8287247214197276} |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cpu
- Datasets 3.5.0
- Tokenizers 0.21.1
- Library
- peft
- License
- apache-2.0
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025