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---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-dog-food
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. -->
# swin-dog-food
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the sasha/dog-food dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0015
- Accuracy: 1.0
## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 53 | 0.0069 | 1.0 |
| 0.0765 | 2.0 | 106 | 0.0032 | 1.0 |
| 0.0765 | 3.0 | 159 | 0.0023 | 1.0 |
| 0.0037 | 4.0 | 212 | 0.0019 | 1.0 |
| 0.0037 | 5.0 | 265 | 0.0018 | 1.0 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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