---
license: apache-2.0
base_model: microsoft/cvt-13
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-13
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9886363636363636
---

<!-- 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. -->

# cvt-13

This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0361
- Accuracy: 0.9886

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4048        | 1.0   | 327  | 0.2161          | 0.9156   |
| 0.33          | 2.0   | 654  | 0.1320          | 0.9501   |
| 0.3147        | 3.0   | 981  | 0.1060          | 0.9612   |
| 0.2213        | 4.0   | 1309 | 0.0820          | 0.9742   |
| 0.3256        | 5.0   | 1636 | 0.0717          | 0.9750   |
| 0.3207        | 6.0   | 1963 | 0.1062          | 0.9626   |
| 0.2273        | 7.0   | 2290 | 0.0535          | 0.9797   |
| 0.2066        | 8.0   | 2618 | 0.0566          | 0.9817   |
| 0.2162        | 9.0   | 2945 | 0.0459          | 0.9828   |
| 0.2296        | 10.0  | 3272 | 0.0444          | 0.9851   |
| 0.187         | 11.0  | 3599 | 0.0348          | 0.9882   |
| 0.2208        | 12.0  | 3927 | 0.0505          | 0.9848   |
| 0.1855        | 13.0  | 4254 | 0.0371          | 0.9869   |
| 0.1875        | 14.0  | 4581 | 0.0384          | 0.9880   |
| 0.202         | 14.99 | 4905 | 0.0361          | 0.9886   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0