File size: 4,319 Bytes
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library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-base-patch4-window8-256-dmae-humeda-DAV15
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-base-patch4-window8-256-dmae-humeda-DAV15
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8423
- 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: 2e-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 | 0.8696 | 5 | 1.5972 | 0.3077 |
| 6.7562 | 1.8696 | 10 | 1.5357 | 0.3077 |
| 6.7562 | 2.8696 | 15 | 1.4954 | 0.4038 |
| 6.2842 | 3.8696 | 20 | 1.4612 | 0.3462 |
| 6.2842 | 4.8696 | 25 | 1.3875 | 0.3269 |
| 4.9858 | 5.8696 | 30 | 1.3370 | 0.3462 |
| 4.9858 | 6.8696 | 35 | 1.2739 | 0.4423 |
| 3.5596 | 7.8696 | 40 | 1.1774 | 0.4808 |
| 3.5596 | 8.8696 | 45 | 1.1214 | 0.4808 |
| 2.6814 | 9.8696 | 50 | 1.0999 | 0.5192 |
| 2.6814 | 10.8696 | 55 | 1.1773 | 0.4615 |
| 2.3236 | 11.8696 | 60 | 0.9874 | 0.5192 |
| 2.3236 | 12.8696 | 65 | 1.1124 | 0.5 |
| 1.8037 | 13.8696 | 70 | 0.8936 | 0.6538 |
| 1.8037 | 14.8696 | 75 | 1.2064 | 0.4423 |
| 1.6474 | 15.8696 | 80 | 0.8423 | 0.75 |
| 1.6474 | 16.8696 | 85 | 1.0134 | 0.6346 |
| 1.5505 | 17.8696 | 90 | 0.8965 | 0.6923 |
| 1.5505 | 18.8696 | 95 | 0.9215 | 0.6538 |
| 1.2697 | 19.8696 | 100 | 1.0155 | 0.6154 |
| 1.2697 | 20.8696 | 105 | 0.8500 | 0.7115 |
| 1.1783 | 21.8696 | 110 | 0.9573 | 0.6538 |
| 1.1783 | 22.8696 | 115 | 0.8915 | 0.6923 |
| 1.0235 | 23.8696 | 120 | 0.9831 | 0.6538 |
| 1.0235 | 24.8696 | 125 | 0.9464 | 0.6538 |
| 0.9706 | 25.8696 | 130 | 0.9413 | 0.6923 |
| 0.9706 | 26.8696 | 135 | 1.0249 | 0.6346 |
| 0.9409 | 27.8696 | 140 | 0.9754 | 0.6538 |
| 0.9409 | 28.8696 | 145 | 0.9530 | 0.7115 |
| 0.9447 | 29.8696 | 150 | 1.0266 | 0.6538 |
| 0.9447 | 30.8696 | 155 | 1.0819 | 0.6538 |
| 0.8352 | 31.8696 | 160 | 0.9922 | 0.6923 |
| 0.8352 | 32.8696 | 165 | 0.9755 | 0.6923 |
| 0.8055 | 33.8696 | 170 | 0.9768 | 0.7115 |
| 0.8055 | 34.8696 | 175 | 0.9950 | 0.6923 |
| 0.7481 | 35.8696 | 180 | 1.0135 | 0.6923 |
| 0.7481 | 36.8696 | 185 | 1.0168 | 0.6923 |
| 0.7483 | 37.8696 | 190 | 1.0091 | 0.6923 |
| 0.7483 | 38.8696 | 195 | 1.0055 | 0.6923 |
| 0.8145 | 39.8696 | 200 | 1.0040 | 0.6923 |
| 0.8145 | 40.8696 | 205 | 1.0039 | 0.6923 |
| 0.7501 | 41.8696 | 210 | 1.0038 | 0.6923 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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