metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_0001_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: 0.9069767441860465
hushem_40x_beit_large_adamax_0001_fold3
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4238
- Accuracy: 0.9070
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: 32
- eval_batch_size: 32
- 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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0397 | 1.0 | 217 | 0.4585 | 0.8605 |
| 0.0001 | 2.0 | 434 | 1.0180 | 0.8837 |
| 0.0 | 3.0 | 651 | 0.9542 | 0.9070 |
| 0.0 | 4.0 | 868 | 1.0472 | 0.9070 |
| 0.011 | 5.0 | 1085 | 0.8152 | 0.8837 |
| 0.0 | 6.0 | 1302 | 0.8047 | 0.9070 |
| 0.0001 | 7.0 | 1519 | 1.1339 | 0.8837 |
| 0.0 | 8.0 | 1736 | 0.6894 | 0.9070 |
| 0.0 | 9.0 | 1953 | 0.9352 | 0.8837 |
| 0.0015 | 10.0 | 2170 | 0.8497 | 0.8372 |
| 0.0 | 11.0 | 2387 | 0.8859 | 0.8837 |
| 0.0 | 12.0 | 2604 | 1.0189 | 0.8837 |
| 0.001 | 13.0 | 2821 | 0.9729 | 0.8605 |
| 0.0 | 14.0 | 3038 | 0.9152 | 0.8837 |
| 0.0 | 15.0 | 3255 | 0.8697 | 0.8605 |
| 0.0 | 16.0 | 3472 | 0.9016 | 0.8605 |
| 0.0 | 17.0 | 3689 | 0.8964 | 0.8837 |
| 0.0 | 18.0 | 3906 | 1.0277 | 0.8837 |
| 0.0 | 19.0 | 4123 | 0.8584 | 0.8837 |
| 0.0 | 20.0 | 4340 | 0.8132 | 0.9070 |
| 0.0 | 21.0 | 4557 | 0.8453 | 0.9070 |
| 0.0 | 22.0 | 4774 | 0.8777 | 0.9070 |
| 0.0 | 23.0 | 4991 | 0.8912 | 0.9070 |
| 0.0 | 24.0 | 5208 | 0.9167 | 0.8837 |
| 0.0 | 25.0 | 5425 | 0.9234 | 0.8837 |
| 0.0 | 26.0 | 5642 | 0.9407 | 0.8837 |
| 0.0 | 27.0 | 5859 | 1.0058 | 0.9070 |
| 0.0 | 28.0 | 6076 | 1.1055 | 0.8837 |
| 0.0 | 29.0 | 6293 | 1.1155 | 0.8837 |
| 0.0 | 30.0 | 6510 | 1.1212 | 0.8837 |
| 0.0 | 31.0 | 6727 | 1.4063 | 0.9070 |
| 0.0 | 32.0 | 6944 | 1.3993 | 0.9070 |
| 0.0 | 33.0 | 7161 | 1.4033 | 0.9070 |
| 0.0 | 34.0 | 7378 | 1.4032 | 0.9070 |
| 0.0 | 35.0 | 7595 | 1.4070 | 0.9070 |
| 0.0 | 36.0 | 7812 | 1.4100 | 0.9070 |
| 0.0 | 37.0 | 8029 | 1.4111 | 0.9070 |
| 0.0 | 38.0 | 8246 | 1.4234 | 0.9070 |
| 0.0 | 39.0 | 8463 | 1.4283 | 0.8837 |
| 0.0 | 40.0 | 8680 | 1.4259 | 0.8837 |
| 0.0 | 41.0 | 8897 | 1.4283 | 0.8837 |
| 0.0 | 42.0 | 9114 | 1.4459 | 0.8837 |
| 0.0 | 43.0 | 9331 | 1.4466 | 0.8837 |
| 0.0 | 44.0 | 9548 | 1.4349 | 0.8837 |
| 0.0 | 45.0 | 9765 | 1.4277 | 0.8837 |
| 0.0 | 46.0 | 9982 | 1.4129 | 0.9070 |
| 0.0 | 47.0 | 10199 | 1.4175 | 0.9070 |
| 0.0 | 48.0 | 10416 | 1.4184 | 0.9070 |
| 0.0 | 49.0 | 10633 | 1.4243 | 0.9070 |
| 0.0 | 50.0 | 10850 | 1.4238 | 0.9070 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2