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

# BirdsSpecies_vit_finetune_LoRA

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: 0.1818

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.2841        | 0.9984 | 468  | 0.3200          |
| 0.2321        | 1.9989 | 937  | 0.2803          |
| 0.2125        | 2.9995 | 1406 | 0.2338          |
| 0.1653        | 4.0    | 1875 | 0.1991          |
| 0.1667        | 4.992  | 2340 | 0.1818          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1