---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 1_lakh_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned
  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. -->

# 1_lakh_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4853
- Accuracy: 0.3370

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.5715        | 1.0000 | 6051  | 2.0155          | 0.2758   |
| 1.6433        | 1.9999 | 12102 | 2.2641          | 0.2734   |
| 1.6866        | 2.9999 | 18153 | 2.1140          | 0.2888   |
| 1.5693        | 4.0    | 24205 | 2.2003          | 0.3066   |
| 1.5371        | 5.0000 | 30256 | 2.2069          | 0.2968   |
| 1.4969        | 5.9999 | 36307 | 2.1547          | 0.3296   |
| 1.4368        | 6.9999 | 42358 | 2.2579          | 0.3250   |
| 1.3077        | 8.0    | 48410 | 2.2327          | 0.3360   |
| 1.3775        | 9.0000 | 54461 | 2.3860          | 0.3400   |
| 1.3595        | 9.9996 | 60510 | 2.4853          | 0.3370   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1