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---
library_name: transformers
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-DAV41
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-DAV41
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: 0.9385
- Accuracy: 0.6818
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 1.4874 | 0.4318 |
| No log | 2.0 | 4 | 1.3560 | 0.4432 |
| No log | 3.0 | 6 | 1.3117 | 0.4432 |
| No log | 4.0 | 8 | 1.2763 | 0.4432 |
| No log | 5.0 | 10 | 1.2602 | 0.5682 |
| 8.9996 | 6.0 | 12 | 1.2348 | 0.6023 |
| 8.9996 | 7.0 | 14 | 1.1982 | 0.5795 |
| 8.9996 | 8.0 | 16 | 1.1592 | 0.6136 |
| 8.9996 | 9.0 | 18 | 1.1142 | 0.625 |
| 8.9996 | 10.0 | 20 | 1.0682 | 0.6364 |
| 8.9996 | 11.0 | 22 | 1.0256 | 0.6477 |
| 7.429 | 12.0 | 24 | 0.9843 | 0.6705 |
| 7.429 | 13.0 | 26 | 0.9602 | 0.6705 |
| 7.429 | 14.0 | 28 | 0.9452 | 0.6591 |
| 7.429 | 15.0 | 30 | 0.9385 | 0.6818 |
| 7.429 | 16.0 | 32 | 0.9320 | 0.6705 |
| 7.429 | 17.0 | 34 | 0.9285 | 0.6477 |
| 6.2752 | 18.0 | 36 | 0.9239 | 0.6591 |
| 6.2752 | 19.0 | 38 | 0.9214 | 0.6818 |
| 6.2752 | 20.0 | 40 | 0.9206 | 0.6818 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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