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# trainer_output

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4766
- Accuracy: 0.5127

## 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: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9670 | 22   | 2.0708          | 0.1449   |
| No log        | 1.9670 | 44   | 2.0653          | 0.1663   |
| 2.0961        | 2.9670 | 66   | 2.0564          | 0.1931   |
| 2.0961        | 3.9670 | 88   | 2.0423          | 0.2350   |
| 2.0586        | 4.9670 | 110  | 2.0171          | 0.2823   |
| 2.0586        | 5.9670 | 132  | 1.9638          | 0.3305   |
| 1.9128        | 6.9670 | 154  | 1.8130          | 0.3968   |
| 1.9128        | 7.9670 | 176  | 1.6647          | 0.4278   |
| 1.9128        | 8.9670 | 198  | 1.5676          | 0.4844   |
| 1.6466        | 9.9670 | 220  | 1.4766          | 0.5127   |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0

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