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_fold1
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: 0.6532717893021993
Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold1
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: 3.0645
- Accuracy: 0.6533
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 |
|---|---|---|---|---|
| 1.1014 | 1.0 | 924 | 1.1155 | 0.6131 |
| 0.917 | 2.0 | 1848 | 1.0767 | 0.6242 |
| 0.7533 | 3.0 | 2772 | 1.0565 | 0.6473 |
| 0.493 | 4.0 | 3696 | 1.1952 | 0.6530 |
| 0.482 | 5.0 | 4620 | 1.3688 | 0.6473 |
| 0.1989 | 6.0 | 5544 | 1.6284 | 0.6435 |
| 0.1622 | 7.0 | 6468 | 2.0114 | 0.6373 |
| 0.0666 | 8.0 | 7392 | 2.2124 | 0.6541 |
| 0.0417 | 9.0 | 8316 | 2.4424 | 0.6389 |
| 0.0196 | 10.0 | 9240 | 2.5614 | 0.6397 |
| 0.0323 | 11.0 | 10164 | 2.8070 | 0.6443 |
| 0.0014 | 12.0 | 11088 | 2.8503 | 0.6506 |
| 0.001 | 13.0 | 12012 | 2.8885 | 0.6497 |
| 0.0706 | 14.0 | 12936 | 3.0224 | 0.6462 |
| 0.0003 | 15.0 | 13860 | 3.0064 | 0.6465 |
| 0.0013 | 16.0 | 14784 | 3.0115 | 0.6552 |
| 0.0316 | 17.0 | 15708 | 3.0514 | 0.6563 |
| 0.0002 | 18.0 | 16632 | 3.0348 | 0.6568 |
| 0.0 | 19.0 | 17556 | 3.0737 | 0.6508 |
| 0.0494 | 20.0 | 18480 | 3.0645 | 0.6533 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1