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distilbert-base-uncased-lora-text-classification
qualis2006/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from qualis2006. 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 16, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Dec 15, 2023
- Updated
- Dec 16, 2023
- SHA
- a1b3ffbd
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: 1.0087
- Accuracy: {'accuracy': 0.886}
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 | 0.3263 | {'accuracy': 0.882} |
| 0.4298 | 2.0 | 500 | 0.4513 | {'accuracy': 0.871} |
| 0.4298 | 3.0 | 750 | 0.6971 | {'accuracy': 0.864} |
| 0.2176 | 4.0 | 1000 | 0.6914 | {'accuracy': 0.877} |
| 0.2176 | 5.0 | 1250 | 0.7609 | {'accuracy': 0.889} |
| 0.095 | 6.0 | 1500 | 0.8447 | {'accuracy': 0.894} |
| 0.095 | 7.0 | 1750 | 0.9361 | {'accuracy': 0.888} |
| 0.024 | 8.0 | 2000 | 0.9976 | {'accuracy': 0.893} |
| 0.024 | 9.0 | 2250 | 1.0071 | {'accuracy': 0.885} |
| 0.0097 | 10.0 | 2500 | 1.0087 | {'accuracy': 0.886} |
Framework versions
- Transformers 4.34.1
- Pytorch 1.13.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- apache-2.0
- Created
- Dec 15, 2023
- Updated
- Dec 16, 2023