---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold3
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.654491341991342
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold3

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6305
- Accuracy: 0.6545

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0933        | 1.0   | 923  | 1.1338          | 0.6069   |
| 0.9991        | 2.0   | 1846 | 1.0315          | 0.6488   |
| 0.8084        | 3.0   | 2769 | 0.9631          | 0.6669   |
| 0.4871        | 4.0   | 3692 | 1.0424          | 0.6650   |
| 0.3928        | 5.0   | 4615 | 1.1438          | 0.6599   |
| 0.2213        | 6.0   | 5538 | 1.2845          | 0.6591   |
| 0.1199        | 7.0   | 6461 | 1.3914          | 0.6553   |
| 0.1231        | 8.0   | 7384 | 1.5372          | 0.6504   |
| 0.1309        | 9.0   | 8307 | 1.6016          | 0.6526   |
| 0.074         | 10.0  | 9230 | 1.6305          | 0.6545   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1