Downloads · 30 days
4
44% of all-time downloads
distilbert-base-uncased-lora-text-classification
RickyLinus/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from RickyLinus. 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
9
Public
Repo size
2.5 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.5 MB · 72%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024
- SHA
- 46f17991
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: 1.0005
- Accuracy: {'accuracy': 0.889}
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.5429 | {'accuracy': 0.833} |
| 0.4379 | 2.0 | 500 | 0.4558 | {'accuracy': 0.878} |
| 0.4379 | 3.0 | 750 | 0.6034 | {'accuracy': 0.876} |
| 0.2125 | 4.0 | 1000 | 0.7067 | {'accuracy': 0.892} |
| 0.2125 | 5.0 | 1250 | 0.8947 | {'accuracy': 0.875} |
| 0.0695 | 6.0 | 1500 | 0.8737 | {'accuracy': 0.886} |
| 0.0695 | 7.0 | 1750 | 0.9554 | {'accuracy': 0.889} |
| 0.0271 | 8.0 | 2000 | 0.9786 | {'accuracy': 0.894} |
| 0.0271 | 9.0 | 2250 | 0.9897 | {'accuracy': 0.893} |
| 0.0052 | 10.0 | 2500 | 1.0005 | {'accuracy': 0.889} |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Nov 9, 2024
- Updated
- Nov 9, 2024