metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-dmae-va-U5-42D
results: []
beit-base-patch16-224-dmae-va-U5-42D
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6193
- Accuracy: 0.7
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: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9 | 7 | 0.8832 | 0.6167 |
| 1.2709 | 1.94 | 15 | 0.8194 | 0.7 |
| 0.9705 | 2.97 | 23 | 0.7715 | 0.6 |
| 0.7033 | 4.0 | 31 | 1.1243 | 0.6333 |
| 0.7033 | 4.9 | 38 | 1.2102 | 0.55 |
| 0.7367 | 5.94 | 46 | 1.0123 | 0.65 |
| 0.5424 | 6.97 | 54 | 1.1218 | 0.6667 |
| 0.3998 | 8.0 | 62 | 1.3493 | 0.6 |
| 0.3998 | 8.9 | 69 | 1.3213 | 0.5833 |
| 0.3478 | 9.94 | 77 | 1.2704 | 0.6167 |
| 0.3467 | 10.97 | 85 | 1.4684 | 0.6167 |
| 0.2805 | 12.0 | 93 | 1.1832 | 0.7167 |
| 0.2496 | 12.9 | 100 | 1.3645 | 0.6333 |
| 0.2496 | 13.94 | 108 | 1.3561 | 0.6667 |
| 0.1855 | 14.97 | 116 | 1.6048 | 0.6167 |
| 0.2162 | 16.0 | 124 | 1.3662 | 0.6833 |
| 0.1833 | 16.9 | 131 | 1.6070 | 0.6667 |
| 0.1833 | 17.94 | 139 | 1.8448 | 0.6 |
| 0.2022 | 18.97 | 147 | 1.3397 | 0.65 |
| 0.1587 | 20.0 | 155 | 1.5272 | 0.65 |
| 0.1991 | 20.9 | 162 | 1.4667 | 0.65 |
| 0.1639 | 21.94 | 170 | 1.3853 | 0.65 |
| 0.1639 | 22.97 | 178 | 1.8195 | 0.6667 |
| 0.1364 | 24.0 | 186 | 1.7032 | 0.6167 |
| 0.1513 | 24.9 | 193 | 1.6734 | 0.65 |
| 0.1197 | 25.94 | 201 | 1.8673 | 0.6 |
| 0.1197 | 26.97 | 209 | 1.9885 | 0.6 |
| 0.1366 | 28.0 | 217 | 1.7329 | 0.6667 |
| 0.0982 | 28.9 | 224 | 1.6177 | 0.7333 |
| 0.0983 | 29.94 | 232 | 1.6226 | 0.7167 |
| 0.1131 | 30.97 | 240 | 1.5967 | 0.7 |
| 0.1131 | 32.0 | 248 | 1.6310 | 0.7 |
| 0.0694 | 32.9 | 255 | 1.6673 | 0.7333 |
| 0.0745 | 33.94 | 263 | 1.6257 | 0.7 |
| 0.058 | 34.97 | 271 | 1.6017 | 0.7167 |
| 0.058 | 36.0 | 279 | 1.6812 | 0.7 |
| 0.055 | 36.9 | 286 | 1.6524 | 0.7 |
| 0.0569 | 37.94 | 294 | 1.6193 | 0.7 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2