---
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: vit-base-patch16-224-in21k-AdaLora
  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. -->

# vit-base-patch16-224-in21k-AdaLora

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3684

## 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: 0.005
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8653        | 1.0   | 74   | 0.4922          |
| 0.7453        | 2.0   | 148  | 0.4185          |
| 0.6864        | 3.0   | 222  | 0.3936          |
| 0.6402        | 4.0   | 296  | 0.3748          |
| 0.6194        | 5.0   | 370  | 0.3684          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.4
- Pytorch 2.2.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1