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distilbert-base-uncased-lora-text-classification
Dai35106/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from Dai35106. 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 11, 2024
- Updated
- Apr 11, 2024
- SHA
- a344d065
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 the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6098
- Accuracy: {'accuracy': 0.37777777777777777}
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 | 405 | 2.0008 | {'accuracy': 0.37037037037037035} |
| 2.0177 | 2.0 | 810 | 2.0349 | {'accuracy': 0.3802469135802469} |
| 1.8336 | 3.0 | 1215 | 2.0526 | {'accuracy': 0.35802469135802467} |
| 1.7547 | 4.0 | 1620 | 2.1418 | {'accuracy': 0.33827160493827163} |
| 1.5832 | 5.0 | 2025 | 2.2398 | {'accuracy': 0.36790123456790125} |
| 1.5832 | 6.0 | 2430 | 2.2712 | {'accuracy': 0.34814814814814815} |
| 1.4297 | 7.0 | 2835 | 2.3660 | {'accuracy': 0.3530864197530864} |
| 1.2579 | 8.0 | 3240 | 2.4898 | {'accuracy': 0.36790123456790125} |
| 1.1612 | 9.0 | 3645 | 2.5870 | {'accuracy': 0.35802469135802467} |
| 0.9591 | 10.0 | 4050 | 2.6098 | {'accuracy': 0.37777777777777777} |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- peft
- License
- apache-2.0
- Created
- Apr 11, 2024
- Updated
- Apr 11, 2024