metadata
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_fold4
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: 0.2857142857142857
hushem_1x_beit_base_sgd_0001_fold4
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: 1.4354
- Accuracy: 0.2857
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 | 1.4991 | 0.2857 |
| 1.6033 | 2.0 | 12 | 1.4950 | 0.2857 |
| 1.6033 | 3.0 | 18 | 1.4913 | 0.2857 |
| 1.56 | 4.0 | 24 | 1.4878 | 0.2857 |
| 1.5624 | 5.0 | 30 | 1.4847 | 0.2857 |
| 1.5624 | 6.0 | 36 | 1.4813 | 0.2857 |
| 1.5652 | 7.0 | 42 | 1.4787 | 0.2857 |
| 1.5652 | 8.0 | 48 | 1.4758 | 0.2857 |
| 1.5644 | 9.0 | 54 | 1.4729 | 0.2857 |
| 1.5444 | 10.0 | 60 | 1.4702 | 0.2857 |
| 1.5444 | 11.0 | 66 | 1.4678 | 0.2857 |
| 1.5307 | 12.0 | 72 | 1.4653 | 0.2857 |
| 1.5307 | 13.0 | 78 | 1.4629 | 0.2857 |
| 1.518 | 14.0 | 84 | 1.4606 | 0.2857 |
| 1.5309 | 15.0 | 90 | 1.4585 | 0.2857 |
| 1.5309 | 16.0 | 96 | 1.4564 | 0.2857 |
| 1.5513 | 17.0 | 102 | 1.4547 | 0.2857 |
| 1.5513 | 18.0 | 108 | 1.4530 | 0.2857 |
| 1.5683 | 19.0 | 114 | 1.4515 | 0.2857 |
| 1.533 | 20.0 | 120 | 1.4498 | 0.2857 |
| 1.533 | 21.0 | 126 | 1.4484 | 0.2857 |
| 1.5308 | 22.0 | 132 | 1.4473 | 0.2857 |
| 1.5308 | 23.0 | 138 | 1.4462 | 0.2857 |
| 1.5033 | 24.0 | 144 | 1.4450 | 0.2857 |
| 1.4859 | 25.0 | 150 | 1.4438 | 0.2857 |
| 1.4859 | 26.0 | 156 | 1.4427 | 0.2857 |
| 1.5126 | 27.0 | 162 | 1.4416 | 0.2857 |
| 1.5126 | 28.0 | 168 | 1.4408 | 0.2857 |
| 1.5334 | 29.0 | 174 | 1.4400 | 0.2857 |
| 1.5073 | 30.0 | 180 | 1.4393 | 0.2857 |
| 1.5073 | 31.0 | 186 | 1.4387 | 0.2857 |
| 1.4951 | 32.0 | 192 | 1.4381 | 0.2857 |
| 1.4951 | 33.0 | 198 | 1.4376 | 0.2857 |
| 1.5148 | 34.0 | 204 | 1.4371 | 0.2857 |
| 1.5182 | 35.0 | 210 | 1.4366 | 0.2857 |
| 1.5182 | 36.0 | 216 | 1.4363 | 0.2857 |
| 1.5025 | 37.0 | 222 | 1.4360 | 0.2857 |
| 1.5025 | 38.0 | 228 | 1.4357 | 0.2857 |
| 1.5134 | 39.0 | 234 | 1.4356 | 0.2857 |
| 1.5013 | 40.0 | 240 | 1.4354 | 0.2857 |
| 1.5013 | 41.0 | 246 | 1.4354 | 0.2857 |
| 1.501 | 42.0 | 252 | 1.4354 | 0.2857 |
| 1.501 | 43.0 | 258 | 1.4354 | 0.2857 |
| 1.5486 | 44.0 | 264 | 1.4354 | 0.2857 |
| 1.4725 | 45.0 | 270 | 1.4354 | 0.2857 |
| 1.4725 | 46.0 | 276 | 1.4354 | 0.2857 |
| 1.4918 | 47.0 | 282 | 1.4354 | 0.2857 |
| 1.4918 | 48.0 | 288 | 1.4354 | 0.2857 |
| 1.5174 | 49.0 | 294 | 1.4354 | 0.2857 |
| 1.5195 | 50.0 | 300 | 1.4354 | 0.2857 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0