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distilbert-base-uncased-lora-text-classification
paduraru2009/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from paduraru2009. 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 16, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 15, 2023
- Updated
- Nov 16, 2023
- SHA
- 7379490b
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: 0.6215
- Accuracy: {'accuracy': 0.8248666666666666}
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 |
|---|---|---|---|---|
| 0.4666 | 1.0 | 7500 | 0.5550 | {'accuracy': 0.8414} |
| 0.537 | 2.0 | 15000 | 0.5152 | {'accuracy': 0.8277666666666667} |
| 0.5576 | 3.0 | 22500 | 0.4929 | {'accuracy': 0.8178} |
| 0.5947 | 4.0 | 30000 | 0.4912 | {'accuracy': 0.8104} |
| 0.5841 | 5.0 | 37500 | 0.5970 | {'accuracy': 0.8050666666666667} |
| 0.6447 | 6.0 | 45000 | 0.6422 | {'accuracy': 0.8114333333333333} |
| 0.5955 | 7.0 | 52500 | 0.5771 | {'accuracy': 0.8209} |
| 0.5419 | 8.0 | 60000 | 0.5765 | {'accuracy': 0.821} |
| 0.5966 | 9.0 | 67500 | 0.6055 | {'accuracy': 0.8230666666666666} |
| 0.5417 | 10.0 | 75000 | 0.6215 | {'accuracy': 0.8248666666666666} |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.13.2
- License
- apache-2.0
- Created
- Nov 15, 2023
- Updated
- Nov 16, 2023