metadata
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finetuned-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: 0.7051282051282052
swinv2-tiny-patch4-window8-256-finetuned-microbes
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0939
- Accuracy: 0.7051
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 |
|---|---|---|---|---|
| 4.1153 | 0.97 | 16 | 3.8048 | 0.1239 |
| 3.2047 | 2.0 | 33 | 2.9123 | 0.2949 |
| 2.6979 | 2.97 | 49 | 2.2162 | 0.4231 |
| 1.9422 | 4.0 | 66 | 1.8476 | 0.5043 |
| 1.5677 | 4.97 | 82 | 1.6194 | 0.5684 |
| 1.3485 | 6.0 | 99 | 1.4825 | 0.5855 |
| 1.146 | 6.97 | 115 | 1.4073 | 0.5983 |
| 1.0408 | 8.0 | 132 | 1.2730 | 0.6325 |
| 0.9334 | 8.97 | 148 | 1.2782 | 0.6282 |
| 0.8702 | 10.0 | 165 | 1.1758 | 0.6752 |
| 0.8589 | 10.97 | 181 | 1.1652 | 0.6838 |
| 0.7607 | 12.0 | 198 | 1.2129 | 0.6795 |
| 0.7676 | 12.97 | 214 | 1.1509 | 0.6795 |
| 0.7359 | 14.0 | 231 | 1.1327 | 0.6966 |
| 0.7491 | 14.97 | 247 | 1.1059 | 0.6966 |
| 0.6664 | 16.0 | 264 | 1.1413 | 0.6923 |
| 0.618 | 16.97 | 280 | 1.0954 | 0.7009 |
| 0.6504 | 18.0 | 297 | 1.1030 | 0.7009 |
| 0.6241 | 18.97 | 313 | 1.0956 | 0.7009 |
| 0.6258 | 19.39 | 320 | 1.0939 | 0.7051 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cpu
- Datasets 2.14.4
- Tokenizers 0.13.3