|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/beit-base-patch16-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: smids_1x_beit_base_rms_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: 0.6978297161936561 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# smids_1x_beit_base_rms_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: 0.7464 |
|
- Accuracy: 0.6978 |
|
|
|
## 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: 0.001 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.1002 | 1.0 | 76 | 0.9320 | 0.5459 | |
|
| 0.9176 | 2.0 | 152 | 0.9156 | 0.4975 | |
|
| 0.8828 | 3.0 | 228 | 1.4808 | 0.3239 | |
|
| 0.9116 | 4.0 | 304 | 0.9182 | 0.5058 | |
|
| 0.9681 | 5.0 | 380 | 0.8261 | 0.5726 | |
|
| 0.8914 | 6.0 | 456 | 0.8412 | 0.5442 | |
|
| 0.8118 | 7.0 | 532 | 0.8070 | 0.5843 | |
|
| 0.7886 | 8.0 | 608 | 0.7873 | 0.6144 | |
|
| 0.8228 | 9.0 | 684 | 0.8018 | 0.5593 | |
|
| 0.7855 | 10.0 | 760 | 0.8650 | 0.5659 | |
|
| 0.7506 | 11.0 | 836 | 0.8105 | 0.5726 | |
|
| 0.8105 | 12.0 | 912 | 0.7718 | 0.5760 | |
|
| 0.7542 | 13.0 | 988 | 0.7814 | 0.6027 | |
|
| 0.8063 | 14.0 | 1064 | 0.7598 | 0.6244 | |
|
| 0.6853 | 15.0 | 1140 | 0.9554 | 0.5526 | |
|
| 0.6995 | 16.0 | 1216 | 0.7869 | 0.6277 | |
|
| 0.7413 | 17.0 | 1292 | 0.7345 | 0.6561 | |
|
| 0.6942 | 18.0 | 1368 | 0.7274 | 0.6511 | |
|
| 0.7698 | 19.0 | 1444 | 0.7431 | 0.6711 | |
|
| 0.7328 | 20.0 | 1520 | 0.7361 | 0.6327 | |
|
| 0.7002 | 21.0 | 1596 | 0.7435 | 0.6427 | |
|
| 0.6967 | 22.0 | 1672 | 0.8269 | 0.6010 | |
|
| 0.651 | 23.0 | 1748 | 0.7688 | 0.6528 | |
|
| 0.6937 | 24.0 | 1824 | 0.7386 | 0.6578 | |
|
| 0.5694 | 25.0 | 1900 | 0.7657 | 0.6277 | |
|
| 0.6705 | 26.0 | 1976 | 0.7210 | 0.6811 | |
|
| 0.5989 | 27.0 | 2052 | 0.7453 | 0.6561 | |
|
| 0.6274 | 28.0 | 2128 | 0.7780 | 0.6578 | |
|
| 0.5748 | 29.0 | 2204 | 0.7338 | 0.6845 | |
|
| 0.6764 | 30.0 | 2280 | 0.7373 | 0.6394 | |
|
| 0.6934 | 31.0 | 2356 | 0.7055 | 0.6845 | |
|
| 0.6007 | 32.0 | 2432 | 0.7394 | 0.6511 | |
|
| 0.5933 | 33.0 | 2508 | 0.7124 | 0.6795 | |
|
| 0.5894 | 34.0 | 2584 | 0.7760 | 0.6711 | |
|
| 0.6837 | 35.0 | 2660 | 0.7002 | 0.6628 | |
|
| 0.5776 | 36.0 | 2736 | 0.7352 | 0.6694 | |
|
| 0.6485 | 37.0 | 2812 | 0.7046 | 0.6878 | |
|
| 0.5352 | 38.0 | 2888 | 0.7058 | 0.6861 | |
|
| 0.577 | 39.0 | 2964 | 0.6974 | 0.7028 | |
|
| 0.5712 | 40.0 | 3040 | 0.7122 | 0.6811 | |
|
| 0.5117 | 41.0 | 3116 | 0.7026 | 0.6845 | |
|
| 0.4908 | 42.0 | 3192 | 0.7187 | 0.7045 | |
|
| 0.4784 | 43.0 | 3268 | 0.7103 | 0.7028 | |
|
| 0.4739 | 44.0 | 3344 | 0.7027 | 0.7162 | |
|
| 0.5942 | 45.0 | 3420 | 0.7242 | 0.6962 | |
|
| 0.4258 | 46.0 | 3496 | 0.7593 | 0.6912 | |
|
| 0.4726 | 47.0 | 3572 | 0.7433 | 0.6895 | |
|
| 0.4422 | 48.0 | 3648 | 0.7412 | 0.6928 | |
|
| 0.4049 | 49.0 | 3724 | 0.7425 | 0.6995 | |
|
| 0.5059 | 50.0 | 3800 | 0.7464 | 0.6978 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
