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# SPIE_MULTICLASS_FACEBOOK_2_4

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1577
- Accuracy: 0.9472

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.6033        | 0.96   | 18   | 0.5320          | 0.8403   |
| 0.3596        | 1.9733 | 37   | 0.2491          | 0.9213   |
| 0.1973        | 2.9867 | 56   | 0.1948          | 0.9354   |
| 0.1588        | 4.0    | 75   | 0.1542          | 0.9494   |
| 0.1333        | 4.8    | 90   | 0.1577          | 0.9472   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

burn through contamination good weld lack of fusion lack of penetration misalignment