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mnist-mobilevit
akahana/mnist-mobilevit
mnist-mobilevit is a machine learning model from akahana. 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 other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- other
- Model type
- mobilevit
- Access
- Public
- Created
- Aug 8, 2024
- Updated
- Aug 8, 2024
- SHA
- 5ae3b1c4
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. -->
mnist-mobilevit
This model is a fine-tuned version of apple/mobilevit-xx-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0185
- Accuracy: 0.9929
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: 0.0008
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.026 | 0.2132 | 100 | 0.0458 | 0.9867 |
| 0.0232 | 0.4264 | 200 | 0.0453 | 0.9867 |
| 0.0277 | 0.6397 | 300 | 0.0484 | 0.9863 |
| 0.0293 | 0.8529 | 400 | 0.0469 | 0.9865 |
| 0.0235 | 1.0661 | 500 | 0.0288 | 0.9899 |
| 0.0203 | 1.2793 | 600 | 0.0253 | 0.9924 |
| 0.0182 | 1.4925 | 700 | 0.0286 | 0.9916 |
| 0.0205 | 1.7058 | 800 | 0.0203 | 0.9935 |
| 0.0162 | 1.9190 | 900 | 0.0238 | 0.9913 |
| 0.0118 | 2.1322 | 1000 | 0.0247 | 0.9916 |
| 0.0121 | 2.3454 | 1100 | 0.0194 | 0.9932 |
| 0.0154 | 2.5586 | 1200 | 0.0194 | 0.9933 |
| 0.015 | 2.7719 | 1300 | 0.0216 | 0.9933 |
| 0.0145 | 2.9851 | 1400 | 0.0238 | 0.9919 |
| 0.0098 | 3.1983 | 1500 | 0.0208 | 0.993 |
| 0.0093 | 3.4115 | 1600 | 0.0218 | 0.9929 |
| 0.0073 | 3.6247 | 1700 | 0.0189 | 0.9933 |
| 0.008 | 3.8380 | 1800 | 0.0194 | 0.9932 |
| 0.006 | 4.0512 | 1900 | 0.0183 | 0.9938 |
| 0.0063 | 4.2644 | 2000 | 0.0184 | 0.9934 |
| 0.0043 | 4.4776 | 2100 | 0.0184 | 0.9932 |
| 0.0035 | 4.6908 | 2200 | 0.0183 | 0.9931 |
| 0.0061 | 4.9041 | 2300 | 0.0184 | 0.9931 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- mobilevit
- License
- other
- Created
- Aug 8, 2024
- Updated
- Aug 8, 2024