---
library_name: transformers
license: apache-2.0
base_model: timm/vit_base_patch16_224.augreg2_in21k_ft_in1k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output
  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. -->

# output

This model is a fine-tuned version of [timm/vit_base_patch16_224.augreg2_in21k_ft_in1k](https://huggingface.co/timm/vit_base_patch16_224.augreg2_in21k_ft_in1k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1798
- Accuracy: 0.9409

## 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: 128
- eval_batch_size: 128
- seed: 42
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8834        | 1.0   | 29   | 0.3203          | 0.9002   |
| 0.3653        | 2.0   | 58   | 0.2524          | 0.9193   |
| 0.2723        | 3.0   | 87   | 0.2100          | 0.9338   |
| 0.177         | 4.0   | 116  | 0.2148          | 0.9362   |
| 0.1662        | 5.0   | 145  | 0.1798          | 0.9409   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0