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---
license: apache-2.0
base_model: NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-student_six_classes-finetuned-student_six_classes
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: 0.83
---
<!-- 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-student_six_classes-finetuned-student_six_classes
This model is a fine-tuned version of [NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes](https://huggingface.co/NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4176
- Accuracy: 0.83
## 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 | 0.9231 | 3 | 0.4943 | 0.78 |
| No log | 1.8462 | 6 | 0.4716 | 0.78 |
| No log | 2.7692 | 9 | 0.4725 | 0.81 |
| 0.3732 | 4.0 | 13 | 0.4678 | 0.78 |
| 0.3732 | 4.9231 | 16 | 0.4779 | 0.78 |
| 0.3732 | 5.8462 | 19 | 0.4564 | 0.79 |
| 0.3459 | 6.7692 | 22 | 0.4556 | 0.82 |
| 0.3459 | 8.0 | 26 | 0.4757 | 0.77 |
| 0.3459 | 8.9231 | 29 | 0.4773 | 0.77 |
| 0.3273 | 9.8462 | 32 | 0.4661 | 0.77 |
| 0.3273 | 10.7692 | 35 | 0.4518 | 0.79 |
| 0.3273 | 12.0 | 39 | 0.4405 | 0.81 |
| 0.2974 | 12.9231 | 42 | 0.4359 | 0.82 |
| 0.2974 | 13.8462 | 45 | 0.4298 | 0.82 |
| 0.2974 | 14.7692 | 48 | 0.4242 | 0.84 |
| 0.2874 | 16.0 | 52 | 0.4199 | 0.84 |
| 0.2874 | 16.9231 | 55 | 0.4185 | 0.83 |
| 0.2874 | 17.8462 | 58 | 0.4179 | 0.83 |
| 0.2737 | 18.4615 | 60 | 0.4176 | 0.83 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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