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# swinv2-tiny-patch4-window8-256-dmae-va-U5-42C

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: 0.7073
- Accuracy: 0.7667

## 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: 1e-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        | 0.9032  | 7    | 1.3926          | 0.35     |
| 1.4087        | 1.9355  | 15   | 1.3365          | 0.4167   |
| 1.3807        | 2.9677  | 23   | 1.2813          | 0.4167   |
| 1.35          | 4.0     | 31   | 1.2407          | 0.4      |
| 1.35          | 4.9032  | 38   | 1.2116          | 0.4833   |
| 1.2933        | 5.9355  | 46   | 1.1653          | 0.4833   |
| 1.2426        | 6.9677  | 54   | 1.1151          | 0.5167   |
| 1.1771        | 8.0     | 62   | 1.0441          | 0.6      |
| 1.1771        | 8.9032  | 69   | 0.9990          | 0.5667   |
| 1.0983        | 9.9355  | 77   | 0.9456          | 0.6333   |
| 1.0338        | 10.9677 | 85   | 0.9160          | 0.6833   |
| 0.9665        | 12.0    | 93   | 0.8940          | 0.6833   |
| 0.9133        | 12.9032 | 100  | 0.8753          | 0.6      |
| 0.9133        | 13.9355 | 108  | 0.8518          | 0.6667   |
| 0.8521        | 14.9677 | 116  | 0.8515          | 0.65     |
| 0.8461        | 16.0    | 124  | 0.8407          | 0.65     |
| 0.808         | 16.9032 | 131  | 0.8218          | 0.65     |
| 0.808         | 17.9355 | 139  | 0.8170          | 0.6833   |
| 0.7779        | 18.9677 | 147  | 0.7972          | 0.7167   |
| 0.758         | 20.0    | 155  | 0.7817          | 0.7333   |
| 0.7416        | 20.9032 | 162  | 0.7678          | 0.7167   |
| 0.7344        | 21.9355 | 170  | 0.7650          | 0.7167   |
| 0.7344        | 22.9677 | 178  | 0.7428          | 0.7333   |
| 0.7091        | 24.0    | 186  | 0.7280          | 0.75     |
| 0.6876        | 24.9032 | 193  | 0.7235          | 0.75     |
| 0.6887        | 25.9355 | 201  | 0.7278          | 0.75     |
| 0.6887        | 26.9677 | 209  | 0.7264          | 0.75     |
| 0.6897        | 28.0    | 217  | 0.7228          | 0.75     |
| 0.6637        | 28.9032 | 224  | 0.7163          | 0.75     |
| 0.6924        | 29.9355 | 232  | 0.7073          | 0.7667   |
| 0.6234        | 30.9677 | 240  | 0.7057          | 0.7667   |
| 0.6234        | 32.0    | 248  | 0.7090          | 0.7667   |
| 0.6652        | 32.9032 | 255  | 0.7052          | 0.7667   |
| 0.6343        | 33.9355 | 263  | 0.7009          | 0.7667   |
| 0.6327        | 34.9677 | 271  | 0.7017          | 0.7667   |
| 0.6327        | 36.0    | 279  | 0.7023          | 0.7667   |
| 0.6339        | 36.9032 | 286  | 0.7027          | 0.7667   |
| 0.6275        | 37.9355 | 294  | 0.7031          | 0.7667   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

avanzada leve moderada no dmae