metadata
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
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 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