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distilbert-base-uncased-lora-text-classification
Samara1/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from Samara1. 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 Dec 15, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 15, 2023
- Updated
- Dec 15, 2023
- SHA
- d6708b1f
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: 0.9937
- Accuracy: {'accuracy': 0.878}
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 | 0.5858 | {'accuracy': 0.839} |
| 0.4248 | 2.0 | 500 | 0.6538 | {'accuracy': 0.832} |
| 0.4248 | 3.0 | 750 | 0.5316 | {'accuracy': 0.88} |
| 0.2198 | 4.0 | 1000 | 0.6755 | {'accuracy': 0.875} |
| 0.2198 | 5.0 | 1250 | 0.8534 | {'accuracy': 0.867} |
| 0.0838 | 6.0 | 1500 | 0.8499 | {'accuracy': 0.88} |
| 0.0838 | 7.0 | 1750 | 0.8912 | {'accuracy': 0.885} |
| 0.0257 | 8.0 | 2000 | 0.9443 | {'accuracy': 0.879} |
| 0.0257 | 9.0 | 2250 | 0.9789 | {'accuracy': 0.88} |
| 0.0018 | 10.0 | 2500 | 0.9937 | {'accuracy': 0.878} |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Dec 15, 2023
- Updated
- Dec 15, 2023