---
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