---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-for-YogaPosesv6
  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. -->

# finetuned-for-YogaPosesv6

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 yoga_pose_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0562
- Accuracy: 0.9938

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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_steps: 500
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.9954        | 0.8772  | 100  | 0.8301          | 0.8505   |
| 0.3505        | 1.7544  | 200  | 0.1881          | 0.9907   |
| 0.1524        | 2.6316  | 300  | 0.0901          | 0.9844   |
| 0.152         | 3.5088  | 400  | 0.1241          | 0.9688   |
| 0.1314        | 4.3860  | 500  | 0.0562          | 0.9938   |
| 0.1187        | 5.2632  | 600  | 0.1232          | 0.9720   |
| 0.0936        | 6.1404  | 700  | 0.0893          | 0.9688   |
| 0.0753        | 7.0175  | 800  | 0.1510          | 0.9626   |
| 0.0155        | 7.8947  | 900  | 0.0536          | 0.9907   |
| 0.0181        | 8.7719  | 1000 | 0.0515          | 0.9907   |
| 0.0037        | 9.6491  | 1100 | 0.0570          | 0.9907   |
| 0.0121        | 10.5263 | 1200 | 0.0570          | 0.9907   |
| 0.0065        | 11.4035 | 1300 | 0.0565          | 0.9907   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3