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distilbert-base-uncased-lora-text-classification
omosaiye/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from omosaiye. 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 28, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 28, 2023
- Updated
- Dec 28, 2023
- SHA
- 853f978b
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: 0.8923
- Accuracy: {'accuracy': 0.895}
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 | 0.5889 | {'accuracy': 0.838} |
| 0.4397 | 2.0 | 500 | 0.5252 | {'accuracy': 0.862} |
| 0.4397 | 3.0 | 750 | 0.6337 | {'accuracy': 0.869} |
| 0.2288 | 4.0 | 1000 | 0.6840 | {'accuracy': 0.881} |
| 0.2288 | 5.0 | 1250 | 0.8608 | {'accuracy': 0.883} |
| 0.0786 | 6.0 | 1500 | 0.7593 | {'accuracy': 0.895} |
| 0.0786 | 7.0 | 1750 | 0.7988 | {'accuracy': 0.892} |
| 0.0299 | 8.0 | 2000 | 0.8439 | {'accuracy': 0.889} |
| 0.0299 | 9.0 | 2250 | 0.8963 | {'accuracy': 0.895} |
| 0.0112 | 10.0 | 2500 | 0.8923 | {'accuracy': 0.895} |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.13.2
- License
- apache-2.0
- Created
- Dec 28, 2023
- Updated
- Dec 28, 2023