---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-dmae-humeda-1
  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. -->

# swinv2-tiny-patch4-window8-256-dmae-humeda-1

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3549
- Accuracy: 0.5

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.5476          | 0.3462   |
| No log        | 2.0   | 4    | 1.4060          | 0.4615   |
| No log        | 3.0   | 6    | 1.4222          | 0.4423   |
| No log        | 4.0   | 8    | 1.4011          | 0.4231   |
| 1.4158        | 5.0   | 10   | 1.3764          | 0.4615   |
| 1.4158        | 6.0   | 12   | 1.3549          | 0.5      |
| 1.4158        | 7.0   | 14   | 1.3302          | 0.5      |
| 1.4158        | 8.0   | 16   | 1.3073          | 0.5      |
| 1.4158        | 9.0   | 18   | 1.2923          | 0.5      |
| 1.2817        | 10.0  | 20   | 1.2863          | 0.5      |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1