|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/beit-base-patch16-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hushem_1x_beit_base_sgd_0001_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: 0.1111111111111111 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# hushem_1x_beit_base_sgd_0001_fold1 |
|
|
|
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.6388 |
|
- Accuracy: 0.1111 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 6 | 1.6742 | 0.1111 | |
|
| 1.4975 | 2.0 | 12 | 1.6721 | 0.1111 | |
|
| 1.4975 | 3.0 | 18 | 1.6701 | 0.1111 | |
|
| 1.4871 | 4.0 | 24 | 1.6683 | 0.1111 | |
|
| 1.4949 | 5.0 | 30 | 1.6664 | 0.1111 | |
|
| 1.4949 | 6.0 | 36 | 1.6646 | 0.1111 | |
|
| 1.4943 | 7.0 | 42 | 1.6628 | 0.1111 | |
|
| 1.4943 | 8.0 | 48 | 1.6613 | 0.1111 | |
|
| 1.5225 | 9.0 | 54 | 1.6596 | 0.1111 | |
|
| 1.4389 | 10.0 | 60 | 1.6582 | 0.1111 | |
|
| 1.4389 | 11.0 | 66 | 1.6569 | 0.1111 | |
|
| 1.4732 | 12.0 | 72 | 1.6557 | 0.1111 | |
|
| 1.4732 | 13.0 | 78 | 1.6545 | 0.1111 | |
|
| 1.4384 | 14.0 | 84 | 1.6534 | 0.1111 | |
|
| 1.4676 | 15.0 | 90 | 1.6523 | 0.1111 | |
|
| 1.4676 | 16.0 | 96 | 1.6513 | 0.1111 | |
|
| 1.4696 | 17.0 | 102 | 1.6502 | 0.1111 | |
|
| 1.4696 | 18.0 | 108 | 1.6492 | 0.1111 | |
|
| 1.4688 | 19.0 | 114 | 1.6483 | 0.1111 | |
|
| 1.4525 | 20.0 | 120 | 1.6474 | 0.1111 | |
|
| 1.4525 | 21.0 | 126 | 1.6467 | 0.1111 | |
|
| 1.4642 | 22.0 | 132 | 1.6459 | 0.1111 | |
|
| 1.4642 | 23.0 | 138 | 1.6451 | 0.1111 | |
|
| 1.4184 | 24.0 | 144 | 1.6445 | 0.1111 | |
|
| 1.4687 | 25.0 | 150 | 1.6439 | 0.1111 | |
|
| 1.4687 | 26.0 | 156 | 1.6433 | 0.1111 | |
|
| 1.4512 | 27.0 | 162 | 1.6428 | 0.1111 | |
|
| 1.4512 | 28.0 | 168 | 1.6422 | 0.1111 | |
|
| 1.4747 | 29.0 | 174 | 1.6417 | 0.1111 | |
|
| 1.4313 | 30.0 | 180 | 1.6412 | 0.1111 | |
|
| 1.4313 | 31.0 | 186 | 1.6408 | 0.1111 | |
|
| 1.4333 | 32.0 | 192 | 1.6405 | 0.1111 | |
|
| 1.4333 | 33.0 | 198 | 1.6401 | 0.1111 | |
|
| 1.4855 | 34.0 | 204 | 1.6398 | 0.1111 | |
|
| 1.4466 | 35.0 | 210 | 1.6396 | 0.1111 | |
|
| 1.4466 | 36.0 | 216 | 1.6394 | 0.1111 | |
|
| 1.4336 | 37.0 | 222 | 1.6392 | 0.1111 | |
|
| 1.4336 | 38.0 | 228 | 1.6390 | 0.1111 | |
|
| 1.4754 | 39.0 | 234 | 1.6389 | 0.1111 | |
|
| 1.4452 | 40.0 | 240 | 1.6388 | 0.1111 | |
|
| 1.4452 | 41.0 | 246 | 1.6388 | 0.1111 | |
|
| 1.4335 | 42.0 | 252 | 1.6388 | 0.1111 | |
|
| 1.4335 | 43.0 | 258 | 1.6388 | 0.1111 | |
|
| 1.4391 | 44.0 | 264 | 1.6388 | 0.1111 | |
|
| 1.4625 | 45.0 | 270 | 1.6388 | 0.1111 | |
|
| 1.4625 | 46.0 | 276 | 1.6388 | 0.1111 | |
|
| 1.4619 | 47.0 | 282 | 1.6388 | 0.1111 | |
|
| 1.4619 | 48.0 | 288 | 1.6388 | 0.1111 | |
|
| 1.4316 | 49.0 | 294 | 1.6388 | 0.1111 | |
|
| 1.4278 | 50.0 | 300 | 1.6388 | 0.1111 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
