metadata
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12to24-192to384-22kto1k-ft
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to24-192to384-22kto1k-ft-microbes
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: 0.7129629629629629
swinv2-large-patch4-window12to24-192to384-22kto1k-ft-microbes
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to24-192to384-22kto1k-ft on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0311
- Accuracy: 0.7130
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.8445 | 0.98 | 15 | 2.8535 | 0.3194 |
| 2.1358 | 1.97 | 30 | 1.9654 | 0.4491 |
| 1.5947 | 2.95 | 45 | 1.4172 | 0.6204 |
| 1.045 | 4.0 | 61 | 1.1698 | 0.6806 |
| 0.985 | 4.98 | 76 | 1.1927 | 0.6852 |
| 0.775 | 5.97 | 91 | 1.1012 | 0.6898 |
| 0.7207 | 6.95 | 106 | 1.0311 | 0.7130 |
| 0.6611 | 7.87 | 120 | 1.0311 | 0.6991 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cpu
- Datasets 2.14.4
- Tokenizers 0.13.3