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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bird-data
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-birds
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: bird-data
type: bird-data
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8214882943143813
---
<!-- 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-tiny-patch4-window7-224-finetuned-birds
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the bird-data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6642
- Accuracy: 0.8215
## 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: 0.0002
- train_batch_size: 72
- eval_batch_size: 72
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 288
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8854 | 0.99 | 74 | 3.0164 | 0.3039 |
| 2.066 | 1.99 | 148 | 1.4849 | 0.6095 |
| 1.5066 | 2.99 | 222 | 1.0624 | 0.7145 |
| 1.1904 | 3.99 | 296 | 0.9347 | 0.7450 |
| 0.9986 | 4.99 | 370 | 0.8415 | 0.7709 |
| 0.9437 | 5.99 | 444 | 0.7713 | 0.7901 |
| 0.8297 | 6.99 | 518 | 0.7216 | 0.8081 |
| 0.7805 | 7.99 | 592 | 0.6856 | 0.8152 |
| 0.6978 | 8.99 | 666 | 0.6642 | 0.8215 |
| 0.6147 | 9.99 | 740 | 0.6525 | 0.8207 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
|