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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: 0.43478260869565216
---
<!-- 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: 1.2103
- Accuracy: 0.4348
## 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: 0.05
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.86 | 3 | 113.8089 | 0.1087 |
| No log | 2.0 | 7 | 719662.6875 | 0.1087 |
| 113.1437 | 2.86 | 10 | 3930.8594 | 0.1087 |
| 113.1437 | 4.0 | 14 | 57703.1484 | 0.1087 |
| 113.1437 | 4.86 | 17 | 1127.0548 | 0.3261 |
| 96.1157 | 6.0 | 21 | 131.2882 | 0.1087 |
| 96.1157 | 6.86 | 24 | 305.9370 | 0.0870 |
| 96.1157 | 8.0 | 28 | 209.0138 | 0.1087 |
| 38.8121 | 8.86 | 31 | 30.6911 | 0.1304 |
| 38.8121 | 10.0 | 35 | 7.7503 | 0.4565 |
| 38.8121 | 10.86 | 38 | 16.1361 | 0.3261 |
| 10.6492 | 12.0 | 42 | 7.8875 | 0.4565 |
| 10.6492 | 12.86 | 45 | 4.8321 | 0.4565 |
| 10.6492 | 14.0 | 49 | 8.2543 | 0.4565 |
| 3.6688 | 14.86 | 52 | 3.3603 | 0.4565 |
| 3.6688 | 16.0 | 56 | 3.9023 | 0.4565 |
| 3.6688 | 16.86 | 59 | 3.6221 | 0.4565 |
| 1.5847 | 18.0 | 63 | 3.2802 | 0.4565 |
| 1.5847 | 18.86 | 66 | 1.8639 | 0.4565 |
| 1.5235 | 20.0 | 70 | 2.5394 | 0.4565 |
| 1.5235 | 20.86 | 73 | 1.4062 | 0.4783 |
| 1.5235 | 22.0 | 77 | 1.4145 | 0.3913 |
| 1.3634 | 22.86 | 80 | 1.3275 | 0.4565 |
| 1.3634 | 24.0 | 84 | 1.3357 | 0.3478 |
| 1.3634 | 24.86 | 87 | 1.4708 | 0.4565 |
| 1.2807 | 26.0 | 91 | 1.2909 | 0.4565 |
| 1.2807 | 26.86 | 94 | 1.3445 | 0.4565 |
| 1.2807 | 28.0 | 98 | 1.2974 | 0.3696 |
| 1.2625 | 28.86 | 101 | 1.3482 | 0.4565 |
| 1.2625 | 30.0 | 105 | 1.2866 | 0.3478 |
| 1.2625 | 30.86 | 108 | 1.2364 | 0.4783 |
| 1.2472 | 32.0 | 112 | 1.2389 | 0.4130 |
| 1.2472 | 32.86 | 115 | 1.2459 | 0.3478 |
| 1.2472 | 34.0 | 119 | 1.2090 | 0.4348 |
| 1.2117 | 34.29 | 120 | 1.2103 | 0.4348 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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