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distilbert-base-uncased-lora-feedback-classification
Philseok/distilbert-base-uncased-lora-feedback-classification
distilbert-base-uncased-lora-feedback-classification is a machine learning model from Philseok. 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
- Mar 1, 2026
- Updated
- Mar 4, 2026
- SHA
- c18c7846
Base models
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-feedback-classification
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: 0.3213
- Accuracy: 0.8757
- Precision: 0.8869
- Recall: 0.9159
- F1: 0.9011
- Roc Auc: 0.9403
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.2968 | 1.0 | 51 | 0.3062 | 0.8815 | 0.8950 | 0.9159 | 0.9053 | 0.9417 |
| 0.3910 | 2.0 | 102 | 0.3117 | 0.8815 | 0.9023 | 0.9065 | 0.9044 | 0.9397 |
| 0.3319 | 3.0 | 153 | 0.3197 | 0.8728 | 0.8864 | 0.9112 | 0.8986 | 0.9409 |
| 0.2811 | 4.0 | 204 | 0.3194 | 0.8757 | 0.8904 | 0.9112 | 0.9007 | 0.9406 |
| 0.2593 | 5.0 | 255 | 0.3213 | 0.8757 | 0.8869 | 0.9159 | 0.9011 | 0.9403 |
Framework versions
- PEFT 0.18.1
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2
- Library
- peft
- License
- apache-2.0
- Created
- Mar 1, 2026
- Updated
- Mar 4, 2026