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distilbert-base-uncased-lora-text-classification
wt-golf/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from wt-golf. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 2, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023
- SHA
- f5f269d5
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: 0.7319
- 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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 334 | 0.3624 | {'accuracy': 0.885} |
| 0.4609 | 2.0 | 668 | 0.4852 | {'accuracy': 0.864} |
| 0.2886 | 3.0 | 1002 | 0.5991 | {'accuracy': 0.882} |
| 0.2886 | 4.0 | 1336 | 0.6573 | {'accuracy': 0.89} |
| 0.0844 | 5.0 | 1670 | 0.7319 | {'accuracy': 0.889} |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- License
- apache-2.0
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023