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distilbert-base-uncased-lora-text-classification
Saurabh54/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from Saurabh54. 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 1, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Oct 31, 2023
- Updated
- Nov 1, 2023
- SHA
- f4c4f8e5
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 the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3734
- Accuracy: {'accuracy': 0.6005221932114883}
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 192 | 1.8883 | {'accuracy': 0.36945169712793735} |
| No log | 2.0 | 384 | 1.6563 | {'accuracy': 0.4216710182767624} |
| 1.8736 | 3.0 | 576 | 1.5385 | {'accuracy': 0.46736292428198434} |
| 1.8736 | 4.0 | 768 | 1.4276 | {'accuracy': 0.5274151436031331} |
| 1.8736 | 5.0 | 960 | 1.3666 | {'accuracy': 0.5613577023498695} |
| 1.2939 | 6.0 | 1152 | 1.3688 | {'accuracy': 0.5613577023498695} |
| 1.2939 | 7.0 | 1344 | 1.3397 | {'accuracy': 0.5783289817232375} |
| 0.9487 | 8.0 | 1536 | 1.3576 | {'accuracy': 0.5757180156657964} |
| 0.9487 | 9.0 | 1728 | 1.3523 | {'accuracy': 0.5939947780678851} |
| 0.9487 | 10.0 | 1920 | 1.3819 | {'accuracy': 0.5926892950391645} |
| 0.7324 | 11.0 | 2112 | 1.3746 | {'accuracy': 0.597911227154047} |
| 0.7324 | 12.0 | 2304 | 1.3734 | {'accuracy': 0.6005221932114883} |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
- License
- apache-2.0
- Created
- Oct 31, 2023
- Updated
- Nov 1, 2023