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---
library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-Ocular-Toxoplasmosis
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8387096774193549
---
<!-- 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-Ocular-Toxoplasmosis
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co./microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5167
- Accuracy: 0.8387
## 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: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.7273 | 2 | 1.4057 | 0.2419 |
| No log | 1.8182 | 5 | 1.2100 | 0.4677 |
| No log | 2.9091 | 8 | 1.1808 | 0.4516 |
| 1.3062 | 4.0 | 11 | 1.0975 | 0.5968 |
| 1.3062 | 4.7273 | 13 | 1.0542 | 0.6613 |
| 1.3062 | 5.8182 | 16 | 0.9857 | 0.6613 |
| 1.3062 | 6.9091 | 19 | 0.9176 | 0.6774 |
| 1.0003 | 8.0 | 22 | 0.8761 | 0.6774 |
| 1.0003 | 8.7273 | 24 | 0.8540 | 0.6774 |
| 1.0003 | 9.8182 | 27 | 0.7777 | 0.6613 |
| 0.8096 | 10.9091 | 30 | 0.7498 | 0.6613 |
| 0.8096 | 12.0 | 33 | 0.7569 | 0.6613 |
| 0.8096 | 12.7273 | 35 | 0.7422 | 0.6774 |
| 0.8096 | 13.8182 | 38 | 0.7278 | 0.7097 |
| 0.6556 | 14.9091 | 41 | 0.6877 | 0.7258 |
| 0.6556 | 16.0 | 44 | 0.6433 | 0.7258 |
| 0.6556 | 16.7273 | 46 | 0.6324 | 0.7419 |
| 0.6556 | 17.8182 | 49 | 0.6390 | 0.7419 |
| 0.5725 | 18.9091 | 52 | 0.6504 | 0.7742 |
| 0.5725 | 20.0 | 55 | 0.6145 | 0.7581 |
| 0.5725 | 20.7273 | 57 | 0.5824 | 0.7903 |
| 0.5057 | 21.8182 | 60 | 0.5476 | 0.8226 |
| 0.5057 | 22.9091 | 63 | 0.5413 | 0.8226 |
| 0.5057 | 24.0 | 66 | 0.5335 | 0.8226 |
| 0.5057 | 24.7273 | 68 | 0.5302 | 0.8226 |
| 0.4945 | 25.8182 | 71 | 0.5231 | 0.8226 |
| 0.4945 | 26.9091 | 74 | 0.5167 | 0.8387 |
| 0.4945 | 28.0 | 77 | 0.5132 | 0.8387 |
| 0.4945 | 28.7273 | 79 | 0.5131 | 0.8387 |
| 0.4883 | 29.0909 | 80 | 0.5131 | 0.8387 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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