---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-RH
  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: 0.8598130841121495
---

<!-- 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-RH

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: 0.4150
- Accuracy: 0.8598

## 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        | 1.0   | 8    | 0.6926          | 0.6262   |
| 0.693         | 2.0   | 16   | 0.6873          | 0.6822   |
| 0.6899        | 3.0   | 24   | 0.6694          | 0.6729   |
| 0.6732        | 4.0   | 32   | 0.6146          | 0.7290   |
| 0.6256        | 5.0   | 40   | 0.7084          | 0.4953   |
| 0.6256        | 6.0   | 48   | 0.6591          | 0.6355   |
| 0.5796        | 7.0   | 56   | 0.5670          | 0.7383   |
| 0.5253        | 8.0   | 64   | 0.5351          | 0.7196   |
| 0.4713        | 9.0   | 72   | 0.4614          | 0.8411   |
| 0.441         | 10.0  | 80   | 0.5826          | 0.7570   |
| 0.441         | 11.0  | 88   | 0.4679          | 0.7850   |
| 0.3803        | 12.0  | 96   | 0.4517          | 0.8411   |
| 0.3513        | 13.0  | 104  | 0.4571          | 0.7757   |
| 0.3043        | 14.0  | 112  | 0.4755          | 0.8037   |
| 0.3172        | 15.0  | 120  | 0.5953          | 0.7944   |
| 0.3172        | 16.0  | 128  | 0.5904          | 0.7383   |
| 0.365         | 17.0  | 136  | 0.4213          | 0.8411   |
| 0.279         | 18.0  | 144  | 0.4572          | 0.8037   |
| 0.3092        | 19.0  | 152  | 0.4181          | 0.8131   |
| 0.2667        | 20.0  | 160  | 0.4117          | 0.8224   |
| 0.2667        | 21.0  | 168  | 0.4349          | 0.8037   |
| 0.261         | 22.0  | 176  | 0.4185          | 0.8037   |
| 0.2638        | 23.0  | 184  | 0.3989          | 0.8131   |
| 0.2269        | 24.0  | 192  | 0.3971          | 0.8318   |
| 0.2431        | 25.0  | 200  | 0.4784          | 0.8037   |
| 0.2431        | 26.0  | 208  | 0.3763          | 0.8318   |
| 0.2111        | 27.0  | 216  | 0.4088          | 0.8411   |
| 0.2087        | 28.0  | 224  | 0.4024          | 0.8318   |
| 0.1645        | 29.0  | 232  | 0.4161          | 0.8318   |
| 0.2137        | 30.0  | 240  | 0.4128          | 0.8131   |
| 0.2137        | 31.0  | 248  | 0.4004          | 0.8411   |
| 0.2207        | 32.0  | 256  | 0.4206          | 0.8224   |
| 0.1544        | 33.0  | 264  | 0.3622          | 0.8505   |
| 0.197         | 34.0  | 272  | 0.4356          | 0.8411   |
| 0.2168        | 35.0  | 280  | 0.4067          | 0.8318   |
| 0.2168        | 36.0  | 288  | 0.3809          | 0.8224   |
| 0.1631        | 37.0  | 296  | 0.3865          | 0.8411   |
| 0.1913        | 38.0  | 304  | 0.4008          | 0.8318   |
| 0.1595        | 39.0  | 312  | 0.3752          | 0.8318   |
| 0.1694        | 40.0  | 320  | 0.4150          | 0.8598   |


### Framework versions

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