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