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---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: segformer-class-classWeights-augmentation
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. -->
# segformer-class-classWeights-augmentation
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: 0.0018
- 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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 | 0.89 | 6 | 0.9811 | 0.5862 |
| 1.0899 | 1.93 | 13 | 0.9601 | 0.5862 |
| 0.7599 | 2.96 | 20 | 0.8930 | 0.6897 |
| 0.7599 | 4.0 | 27 | 0.5230 | 0.7931 |
| 0.3436 | 4.89 | 33 | 0.1652 | 0.9310 |
| 0.1853 | 5.93 | 40 | 0.0544 | 1.0 |
| 0.1853 | 6.96 | 47 | 0.0937 | 0.9655 |
| 0.1839 | 8.0 | 54 | 0.0566 | 0.9655 |
| 0.1772 | 8.89 | 60 | 0.0084 | 1.0 |
| 0.1772 | 9.93 | 67 | 0.0114 | 1.0 |
| 0.1016 | 10.96 | 74 | 0.0039 | 1.0 |
| 0.1534 | 12.0 | 81 | 0.0038 | 1.0 |
| 0.1534 | 12.89 | 87 | 0.0187 | 0.9655 |
| 0.1256 | 13.93 | 94 | 0.0023 | 1.0 |
| 0.1234 | 14.96 | 101 | 0.0016 | 1.0 |
| 0.1234 | 16.0 | 108 | 0.0019 | 1.0 |
| 0.1129 | 16.89 | 114 | 0.0018 | 1.0 |
| 0.17 | 17.78 | 120 | 0.0018 | 1.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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