---
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-base-patch16_fold2
  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: 0.6437837837837838
---

<!-- 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. -->

# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold2

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: 3.1168
- Accuracy: 0.6438

## 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: 0.0001
- 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0678        | 1.0   | 923   | 1.1860          | 0.5962   |
| 0.9795        | 2.0   | 1846  | 1.0466          | 0.6414   |
| 0.6213        | 3.0   | 2769  | 1.0577          | 0.6403   |
| 0.3941        | 4.0   | 3692  | 1.2437          | 0.6424   |
| 0.3011        | 5.0   | 4615  | 1.4589          | 0.6443   |
| 0.1999        | 6.0   | 5538  | 1.7644          | 0.63     |
| 0.039         | 7.0   | 6461  | 1.9747          | 0.64     |
| 0.0664        | 8.0   | 7384  | 2.2470          | 0.6368   |
| 0.0635        | 9.0   | 8307  | 2.4483          | 0.6451   |
| 0.0688        | 10.0  | 9230  | 2.6192          | 0.6516   |
| 0.0389        | 11.0  | 10153 | 2.7333          | 0.6470   |
| 0.0075        | 12.0  | 11076 | 2.8548          | 0.6446   |
| 0.0085        | 13.0  | 11999 | 2.9858          | 0.6416   |
| 0.0018        | 14.0  | 12922 | 2.9790          | 0.6424   |
| 0.0034        | 15.0  | 13845 | 3.0326          | 0.6443   |
| 0.009         | 16.0  | 14768 | 3.0570          | 0.6473   |
| 0.0005        | 17.0  | 15691 | 3.1227          | 0.6419   |
| 0.0           | 18.0  | 16614 | 3.1155          | 0.6449   |
| 0.0002        | 19.0  | 17537 | 3.1130          | 0.6454   |
| 0.0002        | 20.0  | 18460 | 3.1168          | 0.6438   |


### Framework versions

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