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# swinv2-tiny-patch4-window8-256-dmae-humeda-DAV44

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: 0.7302
- Accuracy: 0.75

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 1.0     | 4    | 1.4782          | 0.4659   |
| No log        | 2.0     | 8    | 1.3298          | 0.4432   |
| 4.6468        | 3.0     | 12   | 1.2295          | 0.5341   |
| 4.6468        | 4.0     | 16   | 1.1639          | 0.6477   |
| 4.6468        | 5.0     | 20   | 1.0070          | 0.6477   |
| 3.6233        | 6.0     | 24   | 0.9560          | 0.6477   |
| 3.6233        | 7.0     | 28   | 0.8686          | 0.6932   |
| 3.6233        | 8.0     | 32   | 0.8405          | 0.7045   |
| 2.7642        | 9.0     | 36   | 0.8296          | 0.7045   |
| 2.7642        | 10.0    | 40   | 0.8147          | 0.7159   |
| 2.7642        | 11.0    | 44   | 0.8032          | 0.7386   |
| 2.2276        | 12.0    | 48   | 0.7302          | 0.75     |
| 2.2276        | 13.0    | 52   | 0.7815          | 0.75     |
| 2.2276        | 14.0    | 56   | 0.7365          | 0.7273   |
| 2.0873        | 15.0    | 60   | 0.7417          | 0.75     |
| 2.0873        | 16.0    | 64   | 0.7103          | 0.75     |
| 2.0873        | 17.0    | 68   | 0.7166          | 0.75     |
| 1.7268        | 18.0    | 72   | 0.7360          | 0.7386   |
| 1.7268        | 19.0    | 76   | 0.7432          | 0.7159   |
| 1.7268        | 20.0    | 80   | 0.7206          | 0.7273   |
| 1.602         | 21.0    | 84   | 0.7302          | 0.75     |
| 1.602         | 22.0    | 88   | 0.7332          | 0.7159   |
| 1.602         | 23.0    | 92   | 0.7401          | 0.7045   |
| 1.4229        | 24.0    | 96   | 0.7472          | 0.7273   |
| 1.4229        | 25.0    | 100  | 0.7525          | 0.7273   |
| 1.4229        | 26.0    | 104  | 0.7436          | 0.7273   |
| 1.3233        | 27.0    | 108  | 0.7411          | 0.7273   |
| 1.3233        | 28.0    | 112  | 0.7398          | 0.7273   |
| 1.3233        | 29.0    | 116  | 0.7398          | 0.7159   |
| 1.2076        | 30.0    | 120  | 0.7407          | 0.7273   |
| 1.2076        | 31.0    | 124  | 0.7412          | 0.7273   |
| 1.2076        | 31.6154 | 126  | 0.7412          | 0.7273   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

avanzada avanzada humeda leve moderada no dmae