---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-1k-224-finetuned-hand-final
  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. -->

# convnextv2-tiny-1k-224-finetuned-hand-final

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6638
- Accuracy: 0.7563

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6669        | 1.0   | 14   | 0.6050          | 0.6834   |
| 0.5796        | 2.0   | 28   | 0.5599          | 0.7362   |
| 0.5417        | 3.0   | 42   | 0.5486          | 0.7437   |
| 0.5466        | 4.0   | 56   | 0.5528          | 0.7387   |
| 0.5213        | 5.0   | 70   | 0.5673          | 0.7462   |
| 0.493         | 6.0   | 84   | 0.5432          | 0.7613   |
| 0.5051        | 7.0   | 98   | 0.5457          | 0.7513   |
| 0.4656        | 8.0   | 112  | 0.5444          | 0.7563   |
| 0.4399        | 9.0   | 126  | 0.5430          | 0.7613   |
| 0.4213        | 10.0  | 140  | 0.5507          | 0.7613   |
| 0.4118        | 11.0  | 154  | 0.5619          | 0.7538   |
| 0.4015        | 12.0  | 168  | 0.5383          | 0.7513   |
| 0.3785        | 13.0  | 182  | 0.5567          | 0.7563   |
| 0.3487        | 14.0  | 196  | 0.5972          | 0.7462   |
| 0.3401        | 15.0  | 210  | 0.6059          | 0.7462   |
| 0.3215        | 16.0  | 224  | 0.6051          | 0.7563   |
| 0.3171        | 17.0  | 238  | 0.6228          | 0.7513   |
| 0.2971        | 18.0  | 252  | 0.6529          | 0.7563   |
| 0.3111        | 19.0  | 266  | 0.6309          | 0.7588   |
| 0.2722        | 20.0  | 280  | 0.6444          | 0.7588   |
| 0.2677        | 21.0  | 294  | 0.6373          | 0.7588   |
| 0.2721        | 22.0  | 308  | 0.6393          | 0.7538   |
| 0.2694        | 23.0  | 322  | 0.6382          | 0.7613   |
| 0.2731        | 24.0  | 336  | 0.6543          | 0.7613   |
| 0.257         | 25.0  | 350  | 0.6638          | 0.7563   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3