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distilbert-base-uncased-lora-text-classification
tanjinadnanabir/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from tanjinadnanabir. 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
- Oct 15, 2025
- Updated
- Oct 15, 2025
- SHA
- b5865d9f
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-text-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: 0.4369
- Accuracy: {'accuracy': 0.8268876611418048}
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_FUSED 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 |
|---|---|---|---|---|
| 0.5753 | 1.0 | 10744 | 0.5390 | {'accuracy': 0.7955801104972375} |
| 0.5916 | 2.0 | 21488 | 0.4989 | {'accuracy': 0.8158379373848987} |
| 0.588 | 3.0 | 32232 | 0.4547 | {'accuracy': 0.7937384898710865} |
| 0.5735 | 4.0 | 42976 | 0.4249 | {'accuracy': 0.8029465930018416} |
| 0.5573 | 5.0 | 53720 | 0.4652 | {'accuracy': 0.8066298342541437} |
| 0.5945 | 6.0 | 64464 | 0.4789 | {'accuracy': 0.8176795580110497} |
| 0.5735 | 7.0 | 75208 | 0.4329 | {'accuracy': 0.8416206261510129} |
| 0.5498 | 8.0 | 85952 | 0.4656 | {'accuracy': 0.8176795580110497} |
| 0.5794 | 9.0 | 96696 | 0.4467 | {'accuracy': 0.8176795580110497} |
| 0.5251 | 10.0 | 107440 | 0.4369 | {'accuracy': 0.8268876611418048} |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- peft
- License
- apache-2.0
- Created
- Oct 15, 2025
- Updated
- Oct 15, 2025