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: swinv2-large-patch4-window12-192-22k-augmented
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: 0.8439716312056738
swinv2-large-patch4-window12-192-22k-augmented
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: 0.4230
- Accuracy: 0.8440
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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 | 0.8342 | 0.7447 |
| 1.3135 | 2.0 | 10 | 0.6567 | 0.7872 |
| 1.3135 | 3.0 | 15 | 0.4849 | 0.8227 |
| 0.4762 | 4.0 | 20 | 0.4877 | 0.8440 |
| 0.4762 | 5.0 | 25 | 0.4230 | 0.8440 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1