---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-RD
  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: 0.8618181818181818
---

<!-- 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-RD

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: 0.4005
- Accuracy: 0.8618

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5571        | 0.99  | 40   | 1.5191          | 0.5182   |
| 0.979         | 1.99  | 80   | 0.8953          | 0.7091   |
| 0.8343        | 2.98  | 120  | 0.7520          | 0.7273   |
| 0.7755        | 4.0   | 161  | 0.7223          | 0.7527   |
| 0.7064        | 4.99  | 201  | 0.6760          | 0.74     |
| 0.6296        | 5.99  | 241  | 0.5624          | 0.8018   |
| 0.6387        | 6.98  | 281  | 0.5362          | 0.8073   |
| 0.5793        | 8.0   | 322  | 0.5242          | 0.7964   |
| 0.5723        | 8.99  | 362  | 0.4544          | 0.8309   |
| 0.5897        | 9.99  | 402  | 0.4510          | 0.8273   |
| 0.5443        | 10.98 | 442  | 0.4685          | 0.8055   |
| 0.4959        | 12.0  | 483  | 0.4248          | 0.8255   |
| 0.4743        | 12.99 | 523  | 0.4308          | 0.8309   |
| 0.4679        | 13.99 | 563  | 0.3999          | 0.84     |
| 0.4997        | 14.98 | 603  | 0.4151          | 0.8382   |
| 0.4602        | 16.0  | 644  | 0.4112          | 0.8218   |
| 0.4459        | 16.99 | 684  | 0.4196          | 0.8345   |
| 0.4668        | 17.99 | 724  | 0.4042          | 0.8291   |
| 0.41          | 18.98 | 764  | 0.4112          | 0.8436   |
| 0.4349        | 20.0  | 805  | 0.4120          | 0.8418   |
| 0.4558        | 20.99 | 845  | 0.4554          | 0.8218   |
| 0.3952        | 21.99 | 885  | 0.3775          | 0.8509   |
| 0.3395        | 22.98 | 925  | 0.4027          | 0.84     |
| 0.3525        | 24.0  | 966  | 0.3957          | 0.8509   |
| 0.3497        | 24.99 | 1006 | 0.4020          | 0.8527   |
| 0.3625        | 25.99 | 1046 | 0.3910          | 0.8564   |
| 0.3008        | 26.98 | 1086 | 0.3790          | 0.8582   |
| 0.2907        | 28.0  | 1127 | 0.3831          | 0.8564   |
| 0.3165        | 28.99 | 1167 | 0.4005          | 0.8618   |
| 0.3231        | 29.99 | 1207 | 0.4512          | 0.8327   |
| 0.2819        | 30.98 | 1247 | 0.4228          | 0.8455   |
| 0.2704        | 32.0  | 1288 | 0.4074          | 0.86     |
| 0.2429        | 32.99 | 1328 | 0.4405          | 0.8545   |
| 0.2421        | 33.99 | 1368 | 0.4337          | 0.8527   |
| 0.3039        | 34.98 | 1408 | 0.4628          | 0.8473   |
| 0.2677        | 36.0  | 1449 | 0.4411          | 0.8545   |
| 0.2171        | 36.99 | 1489 | 0.4755          | 0.8618   |
| 0.2268        | 37.99 | 1529 | 0.4506          | 0.86     |
| 0.2378        | 38.98 | 1569 | 0.4633          | 0.8527   |
| 0.2021        | 39.75 | 1600 | 0.4492          | 0.8564   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0