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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-mulder-v-scully-colab2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
<!-- 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-mulder-v-scully-colab2
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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5344
- 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: 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 1 | 0.6899 | 0.5 |
| No log | 2.0 | 2 | 0.6701 | 0.25 |
| No log | 3.0 | 3 | 0.6309 | 0.5 |
| No log | 4.0 | 4 | 0.6049 | 0.5 |
| No log | 5.0 | 5 | 0.5828 | 0.5 |
| No log | 6.0 | 6 | 0.5650 | 0.75 |
| No log | 7.0 | 7 | 0.5486 | 0.75 |
| No log | 8.0 | 8 | 0.5344 | 1.0 |
| No log | 9.0 | 9 | 0.5240 | 1.0 |
| 0.2978 | 10.0 | 10 | 0.5149 | 1.0 |
| 0.2978 | 11.0 | 11 | 0.5066 | 1.0 |
| 0.2978 | 12.0 | 12 | 0.4980 | 1.0 |
| 0.2978 | 13.0 | 13 | 0.4880 | 1.0 |
| 0.2978 | 14.0 | 14 | 0.4699 | 1.0 |
| 0.2978 | 15.0 | 15 | 0.4507 | 1.0 |
| 0.2978 | 16.0 | 16 | 0.4310 | 1.0 |
| 0.2978 | 17.0 | 17 | 0.4155 | 1.0 |
| 0.2978 | 18.0 | 18 | 0.4054 | 1.0 |
| 0.2978 | 19.0 | 19 | 0.3994 | 1.0 |
| 0.1751 | 20.0 | 20 | 0.3970 | 1.0 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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