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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: 0.896551724137931
---
<!-- 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: 0.4768
- Accuracy: 0.8966
## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 | 1.0387 | 0.3103 |
| No log | 2.0 | 3 | 1.0144 | 0.6552 |
| No log | 3.0 | 5 | 0.9570 | 0.7241 |
| No log | 4.0 | 6 | 0.9075 | 0.6552 |
| No log | 5.0 | 7 | 0.8455 | 0.7241 |
| No log | 6.0 | 9 | 0.7622 | 0.7931 |
| 0.4555 | 7.0 | 11 | 0.7067 | 0.7931 |
| 0.4555 | 8.0 | 12 | 0.6745 | 0.8276 |
| 0.4555 | 9.0 | 13 | 0.6108 | 0.8621 |
| 0.4555 | 10.0 | 15 | 0.5319 | 0.8966 |
| 0.4555 | 11.0 | 17 | 0.4943 | 0.8966 |
| 0.4555 | 12.0 | 18 | 0.4896 | 0.8966 |
| 0.4555 | 13.0 | 19 | 0.4820 | 0.8966 |
| 0.2224 | 13.33 | 20 | 0.4768 | 0.8966 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|