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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: image-quality-mobilenetv3 |
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results: [] |
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base_model: |
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- timm/mobilenetv3_large_100.ra_in1k |
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pipeline_tag: image-classification |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# image-quality-mobilenetv3 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0123 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 4.3424 | 1.0 | 36 | 3.0847 | |
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| 0.6173 | 2.0 | 72 | 0.4851 | |
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| 0.1393 | 3.0 | 108 | 0.0988 | |
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| 0.0575 | 4.0 | 144 | 0.0536 | |
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| 0.0388 | 5.0 | 180 | 0.0377 | |
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| 0.0324 | 6.0 | 216 | 0.0320 | |
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| 0.0291 | 7.0 | 252 | 0.0312 | |
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| 0.0255 | 8.0 | 288 | 0.0266 | |
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| 0.023 | 9.0 | 324 | 0.0232 | |
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| 0.0213 | 10.0 | 360 | 0.0214 | |
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| 0.0205 | 11.0 | 396 | 0.0209 | |
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| 0.0193 | 12.0 | 432 | 0.0198 | |
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| 0.0183 | 13.0 | 468 | 0.0191 | |
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| 0.0185 | 14.0 | 504 | 0.0179 | |
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| 0.0175 | 15.0 | 540 | 0.0171 | |
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| 0.0166 | 16.0 | 576 | 0.0186 | |
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| 0.0161 | 17.0 | 612 | 0.0167 | |
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| 0.0164 | 18.0 | 648 | 0.0163 | |
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| 0.0152 | 19.0 | 684 | 0.0160 | |
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| 0.0149 | 20.0 | 720 | 0.0156 | |
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| 0.0151 | 21.0 | 756 | 0.0159 | |
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| 0.0147 | 22.0 | 792 | 0.0153 | |
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| 0.0154 | 23.0 | 828 | 0.0162 | |
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| 0.0147 | 24.0 | 864 | 0.0150 | |
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| 0.0144 | 25.0 | 900 | 0.0147 | |
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| 0.0143 | 26.0 | 936 | 0.0144 | |
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| 0.0144 | 27.0 | 972 | 0.0139 | |
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| 0.0152 | 28.0 | 1008 | 0.0150 | |
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| 0.0129 | 29.0 | 1044 | 0.0134 | |
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| 0.0128 | 30.0 | 1080 | 0.0135 | |
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| 0.0126 | 31.0 | 1116 | 0.0141 | |
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| 0.0131 | 32.0 | 1152 | 0.0145 | |
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| 0.0133 | 33.0 | 1188 | 0.0131 | |
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| 0.0124 | 34.0 | 1224 | 0.0133 | |
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| 0.013 | 35.0 | 1260 | 0.0148 | |
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| 0.0121 | 36.0 | 1296 | 0.0129 | |
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| 0.0116 | 37.0 | 1332 | 0.0127 | |
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| 0.0124 | 38.0 | 1368 | 0.0129 | |
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| 0.0121 | 39.0 | 1404 | 0.0134 | |
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| 0.0121 | 40.0 | 1440 | 0.0128 | |
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| 0.0119 | 41.0 | 1476 | 0.0126 | |
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| 0.0116 | 42.0 | 1512 | 0.0125 | |
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| 0.0118 | 43.0 | 1548 | 0.0126 | |
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| 0.0114 | 44.0 | 1584 | 0.0127 | |
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| 0.0117 | 45.0 | 1620 | 0.0125 | |
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| 0.0116 | 46.0 | 1656 | 0.0127 | |
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| 0.0118 | 47.0 | 1692 | 0.0126 | |
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| 0.0116 | 48.0 | 1728 | 0.0123 | |
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| 0.0114 | 49.0 | 1764 | 0.0123 | |
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| 0.0113 | 50.0 | 1800 | 0.0123 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
