metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_sgd_0001_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: 0.26666666666666666
hushem_5x_beit_base_sgd_0001_fold2
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4185
- Accuracy: 0.2667
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 |
|---|---|---|---|---|
| 1.4965 | 1.0 | 27 | 1.5474 | 0.2667 |
| 1.561 | 2.0 | 54 | 1.5386 | 0.2667 |
| 1.5488 | 3.0 | 81 | 1.5312 | 0.2667 |
| 1.5518 | 4.0 | 108 | 1.5243 | 0.2667 |
| 1.4809 | 5.0 | 135 | 1.5177 | 0.2667 |
| 1.4954 | 6.0 | 162 | 1.5111 | 0.2667 |
| 1.4888 | 7.0 | 189 | 1.5048 | 0.2667 |
| 1.5126 | 8.0 | 216 | 1.4993 | 0.2667 |
| 1.4812 | 9.0 | 243 | 1.4939 | 0.2667 |
| 1.4494 | 10.0 | 270 | 1.4885 | 0.2667 |
| 1.4861 | 11.0 | 297 | 1.4838 | 0.2667 |
| 1.491 | 12.0 | 324 | 1.4794 | 0.2667 |
| 1.4395 | 13.0 | 351 | 1.4751 | 0.2667 |
| 1.4636 | 14.0 | 378 | 1.4709 | 0.2667 |
| 1.4302 | 15.0 | 405 | 1.4673 | 0.2667 |
| 1.4414 | 16.0 | 432 | 1.4635 | 0.2667 |
| 1.4468 | 17.0 | 459 | 1.4602 | 0.2667 |
| 1.4709 | 18.0 | 486 | 1.4571 | 0.2667 |
| 1.4325 | 19.0 | 513 | 1.4542 | 0.2667 |
| 1.4645 | 20.0 | 540 | 1.4515 | 0.2667 |
| 1.4346 | 21.0 | 567 | 1.4487 | 0.2667 |
| 1.4324 | 22.0 | 594 | 1.4459 | 0.2667 |
| 1.3769 | 23.0 | 621 | 1.4436 | 0.2667 |
| 1.3945 | 24.0 | 648 | 1.4414 | 0.2667 |
| 1.415 | 25.0 | 675 | 1.4393 | 0.2667 |
| 1.4371 | 26.0 | 702 | 1.4375 | 0.2667 |
| 1.4355 | 27.0 | 729 | 1.4356 | 0.2667 |
| 1.3979 | 28.0 | 756 | 1.4341 | 0.2667 |
| 1.4061 | 29.0 | 783 | 1.4326 | 0.2667 |
| 1.4573 | 30.0 | 810 | 1.4309 | 0.2667 |
| 1.4027 | 31.0 | 837 | 1.4293 | 0.2667 |
| 1.4089 | 32.0 | 864 | 1.4280 | 0.2667 |
| 1.43 | 33.0 | 891 | 1.4268 | 0.2667 |
| 1.4098 | 34.0 | 918 | 1.4255 | 0.2667 |
| 1.3671 | 35.0 | 945 | 1.4244 | 0.2667 |
| 1.3717 | 36.0 | 972 | 1.4237 | 0.2667 |
| 1.3658 | 37.0 | 999 | 1.4228 | 0.2667 |
| 1.4295 | 38.0 | 1026 | 1.4220 | 0.2667 |
| 1.3909 | 39.0 | 1053 | 1.4214 | 0.2667 |
| 1.3599 | 40.0 | 1080 | 1.4209 | 0.2667 |
| 1.3564 | 41.0 | 1107 | 1.4202 | 0.2667 |
| 1.3635 | 42.0 | 1134 | 1.4197 | 0.2667 |
| 1.3875 | 43.0 | 1161 | 1.4194 | 0.2667 |
| 1.3551 | 44.0 | 1188 | 1.4191 | 0.2667 |
| 1.3825 | 45.0 | 1215 | 1.4188 | 0.2667 |
| 1.3691 | 46.0 | 1242 | 1.4187 | 0.2667 |
| 1.3678 | 47.0 | 1269 | 1.4186 | 0.2667 |
| 1.4155 | 48.0 | 1296 | 1.4185 | 0.2667 |
| 1.3778 | 49.0 | 1323 | 1.4185 | 0.2667 |
| 1.3456 | 50.0 | 1350 | 1.4185 | 0.2667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0