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distilbert-base-uncased-lora-text-classification
Rvk4/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from Rvk4. 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
- Jul 23, 2024
- Updated
- Jul 24, 2024
- SHA
- aadc0b71
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: 0.3504
- Accuracy: {'accuracy': 0.9220420199041651}
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 |
|---|---|---|---|---|
| 0.4389 | 1.0 | 5426 | 0.3219 | {'accuracy': 0.8962403243641726} |
| 0.3786 | 2.0 | 10852 | 0.3866 | {'accuracy': 0.8938444526354589} |
| 0.4217 | 3.0 | 16278 | 0.3720 | {'accuracy': 0.8986361960928861} |
| 0.4178 | 4.0 | 21704 | 0.4612 | {'accuracy': 0.8936601548101732} |
| 0.3867 | 5.0 | 27130 | 0.4108 | {'accuracy': 0.9001105786951714} |
| 0.4258 | 6.0 | 32556 | 0.4565 | {'accuracy': 0.9034279395503133} |
| 0.4024 | 7.0 | 37982 | 0.4088 | {'accuracy': 0.9102469590858828} |
| 0.3556 | 8.0 | 43408 | 0.3828 | {'accuracy': 0.9130114264651678} |
| 0.3249 | 9.0 | 48834 | 0.3434 | {'accuracy': 0.9194618503501659} |
| 0.2882 | 10.0 | 54260 | 0.3504 | {'accuracy': 0.9220420199041651} |
Framework versions
- PEFT 0.11.1
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.15.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 23, 2024
- Updated
- Jul 24, 2024