metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-large-patch4-window12-384-in22k-respirator
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: 1
swin-large-patch4-window12-384-in22k-respirator
This model is a fine-tuned version of microsoft/swin-large-patch4-window12-384-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4272
- Accuracy: 1.0
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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 5 | 0.9598 | 0.4074 |
| 0.9359 | 2.0 | 10 | 0.4272 | 1.0 |
| 0.9359 | 3.0 | 15 | 0.2660 | 0.8889 |
| 0.3813 | 4.0 | 20 | 0.1257 | 1.0 |
| 0.3813 | 5.0 | 25 | 0.1451 | 1.0 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2