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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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