metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
- aytvill/plastic-recycling-codes
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
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: 0.391304347826087
widget:
- src: >-
https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image1.jpg
example_title: image1.jpg
- src: >-
https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image2.jpg
example_title: image2.jpg
- src: >-
https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image3.jpg
example_title: image3.jpg
language:
- en
pipeline_tag: image-classification
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
More information needed
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-5
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 5 | 1.847501 | 0.260870 |
| 1.9354 | 2.0 | 10 | 1.729485 | 0.333333 |
| 1.9354 | 3.0 | 15 | 1.681863 | 0.391304 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3