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SF-DMAE-DA
Augusto777/SF-DMAE-DA
SF-DMAE-DA is a machine learning model from Augusto777. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- swiftformer
- Access
- Public
- Created
- Dec 4, 2024
- Updated
- Dec 4, 2024
- SHA
- ec5c0229
Base models
Datasets
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. -->
SF-DMAE-DA
This model is a fine-tuned version of MBZUAI/swiftformer-xs on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8371
- Accuracy: 0.8261
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.15
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3856 | 0.96 | 11 | 1.3864 | 0.1304 |
| 1.376 | 2.0 | 23 | 1.3770 | 0.1522 |
| 1.3201 | 2.96 | 34 | 1.3578 | 0.2609 |
| 1.2272 | 4.0 | 46 | 1.3456 | 0.2174 |
| 1.0812 | 4.96 | 57 | 1.3423 | 0.4348 |
| 1.0301 | 6.0 | 69 | 1.2316 | 0.4130 |
| 0.8375 | 6.96 | 80 | 1.1414 | 0.5 |
| 0.806 | 8.0 | 92 | 1.1792 | 0.4348 |
| 0.6895 | 8.96 | 103 | 1.0475 | 0.5 |
| 0.6142 | 10.0 | 115 | 0.9662 | 0.6522 |
| 0.5602 | 10.96 | 126 | 1.0034 | 0.6739 |
| 0.6118 | 12.0 | 138 | 0.9099 | 0.6087 |
| 0.56 | 12.96 | 149 | 0.9165 | 0.7609 |
| 0.4118 | 14.0 | 161 | 0.8947 | 0.7826 |
| 0.4115 | 14.96 | 172 | 0.9526 | 0.7391 |
| 0.4596 | 16.0 | 184 | 1.0376 | 0.6957 |
| 0.4066 | 16.96 | 195 | 0.8371 | 0.8261 |
| 0.3437 | 18.0 | 207 | 0.9002 | 0.8043 |
| 0.3279 | 18.96 | 218 | 0.8110 | 0.8043 |
| 0.3039 | 20.0 | 230 | 0.6589 | 0.8043 |
| 0.2315 | 20.96 | 241 | 0.8245 | 0.8261 |
| 0.2588 | 22.0 | 253 | 0.8610 | 0.7826 |
| 0.1889 | 22.96 | 264 | 0.7608 | 0.8043 |
| 0.2326 | 24.0 | 276 | 0.8180 | 0.8261 |
| 0.2107 | 24.96 | 287 | 0.8907 | 0.8261 |
| 0.1917 | 26.0 | 299 | 0.8404 | 0.7826 |
| 0.2 | 26.96 | 310 | 0.8136 | 0.7826 |
| 0.194 | 28.0 | 322 | 0.8591 | 0.7609 |
| 0.21 | 28.96 | 333 | 0.8823 | 0.8261 |
| 0.1917 | 30.0 | 345 | 0.7817 | 0.7609 |
| 0.1342 | 30.96 | 356 | 0.8810 | 0.8043 |
| 0.1185 | 32.0 | 368 | 0.9961 | 0.8043 |
| 0.1805 | 32.96 | 379 | 0.9183 | 0.8043 |
| 0.1548 | 34.0 | 391 | 0.9017 | 0.8261 |
| 0.1276 | 34.96 | 402 | 0.9056 | 0.8043 |
| 0.186 | 36.0 | 414 | 0.9376 | 0.8043 |
| 0.135 | 36.96 | 425 | 0.9160 | 0.8043 |
| 0.1313 | 38.0 | 437 | 0.8822 | 0.8043 |
| 0.1628 | 38.26 | 440 | 0.8337 | 0.8261 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
- Type
- swiftformer
- Created
- Dec 4, 2024
- Updated
- Dec 4, 2024