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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swiftformer-xs-DMAE
This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 113.8184
- 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: 0.0003
- 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: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.86 | 3 | 113.8184 | 0.1087 |
| No log | 2.0 | 7 | 113.8094 | 0.1087 |
| 114.0867 | 2.86 | 10 | 113.7944 | 0.1087 |
| 114.0867 | 4.0 | 14 | 113.7881 | 0.1087 |
| 114.0867 | 4.86 | 17 | 113.7100 | 0.1087 |
| 113.3425 | 6.0 | 21 | 113.5884 | 0.1087 |
| 113.3425 | 6.86 | 24 | 113.4998 | 0.1087 |
| 113.3425 | 8.0 | 28 | 113.0578 | 0.1087 |
| 111.228 | 8.86 | 31 | 112.8053 | 0.1087 |
| 111.228 | 10.0 | 35 | 112.5202 | 0.1087 |
| 111.228 | 10.86 | 38 | 112.5811 | 0.1087 |
| 114.9647 | 12.0 | 42 | 112.6090 | 0.1087 |
| 114.9647 | 12.86 | 45 | 112.4973 | 0.1087 |
| 114.9647 | 14.0 | 49 | 111.9761 | 0.1087 |
| 110.7738 | 14.86 | 52 | 111.8117 | 0.1087 |
| 110.7738 | 16.0 | 56 | 111.6589 | 0.1087 |
| 110.7738 | 16.86 | 59 | 111.5367 | 0.1087 |
| 111.0505 | 18.0 | 63 | 111.7016 | 0.1087 |
| 111.0505 | 18.86 | 66 | 111.9068 | 0.1087 |
| 111.4545 | 20.0 | 70 | 111.6203 | 0.1087 |
| 111.4545 | 20.86 | 73 | 111.1266 | 0.1087 |
| 111.4545 | 22.0 | 77 | 110.2879 | 0.1087 |
| 111.2779 | 22.86 | 80 | 109.8523 | 0.1087 |
| 111.2779 | 24.0 | 84 | 109.5283 | 0.1087 |
| 111.2779 | 24.86 | 87 | 109.9590 | 0.1087 |
| 110.5166 | 26.0 | 91 | 109.9752 | 0.1087 |
| 110.5166 | 26.86 | 94 | 109.5435 | 0.1087 |
| 110.5166 | 28.0 | 98 | 109.5712 | 0.1087 |
| 108.66 | 28.86 | 101 | 108.8924 | 0.1087 |
| 108.66 | 30.0 | 105 | 108.3990 | 0.1087 |
| 108.66 | 30.86 | 108 | 108.7050 | 0.1087 |
| 109.688 | 32.0 | 112 | 108.7237 | 0.1087 |
| 109.688 | 32.86 | 115 | 109.0679 | 0.1087 |
| 109.688 | 34.0 | 119 | 108.5750 | 0.1087 |
| 109.4549 | 34.29 | 120 | 108.5167 | 0.1087 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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