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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
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