Downloads · 30 days
7
30% of all-time downloads
distilbert-base-uncased-lora-text-classification
sankar12345/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from sankar12345. 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. --
All-time downloads
23
Public
Parameters
67.6M
275 MB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors273 MB · 100%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jul 27, 2024
- Updated
- Mar 25, 2025
- SHA
- 964f6017
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: 0.6084
- Accuracy: {'accuracy': 0.896}
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3456 | {'accuracy': 0.889} |
| 0.3995 | 2.0 | 500 | 0.5733 | {'accuracy': 0.862} |
| 0.3995 | 3.0 | 750 | 0.5510 | {'accuracy': 0.896} |
| 0.1311 | 4.0 | 1000 | 0.6322 | {'accuracy': 0.886} |
| 0.1311 | 5.0 | 1250 | 0.6084 | {'accuracy': 0.896} |
Framework versions
- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 27, 2024
- Updated
- Mar 25, 2025