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-DMAE-5e-1
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: 0.45652173913043476
swinv2-tiny-patch4-window8-256-DMAE-5e-1
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: 54.3349
- Accuracy: 0.4565
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: 0.5
- 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 | 343.8003 | 0.3261 |
| No log | 2.0 | 7 | 1260.1489 | 0.1087 |
| 517.6714 | 2.86 | 10 | 457.5103 | 0.3261 |
| 517.6714 | 4.0 | 14 | 180.1205 | 0.1087 |
| 517.6714 | 4.86 | 17 | 190.9627 | 0.1087 |
| 201.7487 | 6.0 | 21 | 54.3349 | 0.4565 |
| 201.7487 | 6.86 | 24 | 70.2849 | 0.3261 |
| 201.7487 | 8.0 | 28 | 57.7033 | 0.3261 |
| 64.7194 | 8.86 | 31 | 115.5257 | 0.1087 |
| 64.7194 | 10.0 | 35 | 72.7990 | 0.3261 |
| 64.7194 | 10.86 | 38 | 41.8670 | 0.4565 |
| 58.6249 | 12.0 | 42 | 26.2765 | 0.4565 |
| 58.6249 | 12.86 | 45 | 41.7245 | 0.3261 |
| 58.6249 | 14.0 | 49 | 23.6962 | 0.4565 |
| 49.7372 | 14.86 | 52 | 13.4265 | 0.3261 |
| 49.7372 | 16.0 | 56 | 7.0405 | 0.4565 |
| 49.7372 | 16.86 | 59 | 5.0777 | 0.4565 |
| 11.7669 | 18.0 | 63 | 13.5690 | 0.4565 |
| 11.7669 | 18.86 | 66 | 5.5425 | 0.1087 |
| 13.3323 | 20.0 | 70 | 6.4491 | 0.4565 |
| 13.3323 | 20.86 | 73 | 7.3066 | 0.3261 |
| 13.3323 | 22.0 | 77 | 10.8431 | 0.4565 |
| 9.2763 | 22.86 | 80 | 12.1588 | 0.3261 |
| 9.2763 | 24.0 | 84 | 5.4926 | 0.4565 |
| 9.2763 | 24.86 | 87 | 4.4689 | 0.3261 |
| 6.8526 | 26.0 | 91 | 3.7880 | 0.4565 |
| 6.8526 | 26.86 | 94 | 2.3297 | 0.4565 |
| 6.8526 | 28.0 | 98 | 2.8532 | 0.4565 |
| 3.0687 | 28.86 | 101 | 2.6943 | 0.1087 |
| 3.0687 | 30.0 | 105 | 2.0957 | 0.3261 |
| 3.0687 | 30.86 | 108 | 1.4001 | 0.4565 |
| 2.1059 | 32.0 | 112 | 1.3081 | 0.3261 |
| 2.1059 | 32.86 | 115 | 1.2392 | 0.3261 |
| 2.1059 | 34.0 | 119 | 1.2510 | 0.4565 |
| 1.3417 | 34.29 | 120 | 1.2338 | 0.4565 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0