| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: timm/mobilenetv3_large_100.ra_in1k |
| tags: |
| - timm |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: material-surface-classifier |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # material-surface-classifier |
|
|
| This model is a fine-tuned version of [timm/mobilenetv3_large_100.ra_in1k](https://huggingface.co/timm/mobilenetv3_large_100.ra_in1k) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5208 |
| - Accuracy: 0.83 |
| - F1 Macro: 0.7133 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 15 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 1.3096 | 1.0 | 25 | 1.1979 | 0.54 | 0.4446 | |
| | 0.7334 | 2.0 | 50 | 0.6755 | 0.7075 | 0.6149 | |
| | 0.6720 | 3.0 | 75 | 0.5615 | 0.75 | 0.6328 | |
| | 0.5520 | 4.0 | 100 | 0.4911 | 0.7875 | 0.6849 | |
| | 0.5370 | 5.0 | 125 | 0.4791 | 0.7875 | 0.6668 | |
| | 0.4934 | 6.0 | 150 | 0.4929 | 0.825 | 0.7121 | |
| | 0.4253 | 7.0 | 175 | 0.4966 | 0.8325 | 0.7120 | |
| | 0.3215 | 8.0 | 200 | 0.4997 | 0.8175 | 0.7296 | |
| | 0.3122 | 9.0 | 225 | 0.4815 | 0.835 | 0.7263 | |
| | 0.2824 | 10.0 | 250 | 0.4749 | 0.83 | 0.7124 | |
| | 0.2727 | 11.0 | 275 | 0.5188 | 0.835 | 0.7255 | |
| | 0.1778 | 12.0 | 300 | 0.4973 | 0.8225 | 0.7058 | |
| | 0.2922 | 13.0 | 325 | 0.4867 | 0.8425 | 0.7355 | |
| | 0.2612 | 14.0 | 350 | 0.5655 | 0.85 | 0.7334 | |
| | 0.2593 | 15.0 | 375 | 0.5208 | 0.83 | 0.7133 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.7.0 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
