metadata
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12-192-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Psoriasis-500-100-224-swinv2-large
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8262008733624454
Psoriasis-500-100-224-swinv2-large
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12-192-22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2393
- Accuracy: 0.8262
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4281 | 0.9973 | 92 | 0.7147 | 0.7747 |
| 0.2234 | 1.9946 | 184 | 0.8100 | 0.7930 |
| 0.1221 | 2.9919 | 276 | 0.9876 | 0.7843 |
| 0.0639 | 4.0 | 369 | 1.0562 | 0.7869 |
| 0.0124 | 4.9973 | 461 | 1.2498 | 0.7869 |
| 0.026 | 5.9946 | 553 | 1.2058 | 0.8052 |
| 0.0014 | 6.9919 | 645 | 1.3110 | 0.8061 |
| 0.0007 | 8.0 | 738 | 1.2566 | 0.8210 |
| 0.0058 | 8.9973 | 830 | 1.2338 | 0.8218 |
| 0.0056 | 9.9729 | 920 | 1.2393 | 0.8262 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1