metadata
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-DMAE
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: 0.10869565217391304
swiftformer-xs-DMAE
This model is a fine-tuned version of MBZUAI/swiftformer-xs on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 113.8883
- Accuracy: 0.1087
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: 2.5e-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
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.86 | 3 | 113.8883 | 0.1087 |
| No log | 2.0 | 7 | 113.8868 | 0.1087 |
| 114.1606 | 2.86 | 10 | 113.8851 | 0.1087 |
| 114.1606 | 4.0 | 14 | 113.8846 | 0.1087 |
| 114.1606 | 4.86 | 17 | 113.8832 | 0.1087 |
| 113.5172 | 6.0 | 21 | 113.8808 | 0.1087 |
| 113.5172 | 6.86 | 24 | 113.8795 | 0.1087 |
| 113.5172 | 8.0 | 28 | 113.8794 | 0.1087 |
| 111.7557 | 8.86 | 31 | 113.8766 | 0.1087 |
| 111.7557 | 10.0 | 35 | 113.8747 | 0.1087 |
| 111.7557 | 10.86 | 38 | 113.8735 | 0.1087 |
| 115.9434 | 12.0 | 42 | 113.8712 | 0.1087 |
| 115.9434 | 12.86 | 45 | 113.8699 | 0.1087 |
| 115.9434 | 14.0 | 49 | 113.8671 | 0.1087 |
| 112.3427 | 14.86 | 52 | 113.8607 | 0.1087 |
| 112.3427 | 16.0 | 56 | 113.8567 | 0.1087 |
| 112.3427 | 16.86 | 59 | 113.8570 | 0.1087 |
| 113.2123 | 18.0 | 63 | 113.8532 | 0.1087 |
| 113.2123 | 18.86 | 66 | 113.8511 | 0.1087 |
| 114.0835 | 20.0 | 70 | 113.8500 | 0.1087 |
| 114.0835 | 20.86 | 73 | 113.8469 | 0.1087 |
| 114.0835 | 22.0 | 77 | 113.8450 | 0.1087 |
| 114.5528 | 22.86 | 80 | 113.8422 | 0.1087 |
| 114.5528 | 24.0 | 84 | 113.8341 | 0.1087 |
| 114.5528 | 24.86 | 87 | 113.8315 | 0.1087 |
| 114.5432 | 26.0 | 91 | 113.8268 | 0.1087 |
| 114.5432 | 26.86 | 94 | 113.8247 | 0.1087 |
| 114.5432 | 28.0 | 98 | 113.8250 | 0.1087 |
| 112.7825 | 28.86 | 101 | 113.8207 | 0.1087 |
| 112.7825 | 30.0 | 105 | 113.8155 | 0.1087 |
| 112.7825 | 30.86 | 108 | 113.8183 | 0.1087 |
| 114.2965 | 32.0 | 112 | 113.8187 | 0.1087 |
| 114.2965 | 32.86 | 115 | 113.8187 | 0.1087 |
| 114.2965 | 34.0 | 119 | 113.8124 | 0.1087 |
| 114.0925 | 34.29 | 120 | 113.8146 | 0.1087 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0