---
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-va-U5-42
  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-va-U5-42

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: 0.6806
- Accuracy: 0.8333

## 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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3299          | 0.4      |
| 1.3678        | 1.94  | 15   | 1.2662          | 0.45     |
| 1.3678        | 2.97  | 23   | 1.0959          | 0.5167   |
| 1.2546        | 4.0   | 31   | 0.9759          | 0.55     |
| 1.0271        | 4.9   | 38   | 0.9375          | 0.5667   |
| 1.0271        | 5.94  | 46   | 0.8728          | 0.6      |
| 0.8075        | 6.97  | 54   | 0.7360          | 0.7167   |
| 0.7026        | 8.0   | 62   | 0.8097          | 0.6667   |
| 0.7026        | 8.9   | 69   | 0.7074          | 0.7      |
| 0.5711        | 9.94  | 77   | 0.6913          | 0.7833   |
| 0.5063        | 10.97 | 85   | 0.7462          | 0.7167   |
| 0.5063        | 12.0  | 93   | 0.8509          | 0.5833   |
| 0.4701        | 12.9  | 100  | 0.6895          | 0.7333   |
| 0.3708        | 13.94 | 108  | 0.7593          | 0.6833   |
| 0.3708        | 14.97 | 116  | 0.8622          | 0.7167   |
| 0.3581        | 16.0  | 124  | 0.7504          | 0.7667   |
| 0.3581        | 16.9  | 131  | 0.6694          | 0.75     |
| 0.3342        | 17.94 | 139  | 0.7262          | 0.7333   |
| 0.2979        | 18.97 | 147  | 0.7234          | 0.7167   |
| 0.2979        | 20.0  | 155  | 0.6403          | 0.7833   |
| 0.2919        | 20.9  | 162  | 0.6847          | 0.7667   |
| 0.274         | 21.94 | 170  | 0.6943          | 0.75     |
| 0.274         | 22.97 | 178  | 0.7235          | 0.7833   |
| 0.2434        | 24.0  | 186  | 0.7836          | 0.75     |
| 0.239         | 24.9  | 193  | 0.7199          | 0.8167   |
| 0.239         | 25.94 | 201  | 0.6806          | 0.8333   |
| 0.2184        | 26.97 | 209  | 0.6923          | 0.8      |
| 0.2176        | 28.0  | 217  | 0.7070          | 0.7833   |
| 0.2176        | 28.9  | 224  | 0.6991          | 0.7667   |
| 0.231         | 29.94 | 232  | 0.7043          | 0.7833   |
| 0.1889        | 30.97 | 240  | 0.6575          | 0.7667   |
| 0.1889        | 32.0  | 248  | 0.7521          | 0.75     |
| 0.2033        | 32.9  | 255  | 0.7062          | 0.7833   |
| 0.2033        | 33.94 | 263  | 0.6958          | 0.8      |
| 0.1891        | 34.97 | 271  | 0.7189          | 0.8      |
| 0.1739        | 36.0  | 279  | 0.7457          | 0.8      |
| 0.1739        | 36.9  | 286  | 0.7766          | 0.7833   |
| 0.1949        | 37.94 | 294  | 0.7808          | 0.7667   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2