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_001_fold5
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: 0.43902439024390244
hushem_1x_beit_base_sgd_001_fold5
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: 1.3101
- Accuracy: 0.4390
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.5856 | 0.2439 |
| 1.5446 | 2.0 | 12 | 1.5524 | 0.2683 |
| 1.5446 | 3.0 | 18 | 1.5246 | 0.3171 |
| 1.4921 | 4.0 | 24 | 1.5015 | 0.3171 |
| 1.4491 | 5.0 | 30 | 1.4859 | 0.3415 |
| 1.4491 | 6.0 | 36 | 1.4721 | 0.3415 |
| 1.4253 | 7.0 | 42 | 1.4615 | 0.3415 |
| 1.4253 | 8.0 | 48 | 1.4471 | 0.3659 |
| 1.3656 | 9.0 | 54 | 1.4347 | 0.3902 |
| 1.3889 | 10.0 | 60 | 1.4270 | 0.3902 |
| 1.3889 | 11.0 | 66 | 1.4192 | 0.4146 |
| 1.3303 | 12.0 | 72 | 1.4108 | 0.4146 |
| 1.3303 | 13.0 | 78 | 1.4040 | 0.4146 |
| 1.3227 | 14.0 | 84 | 1.3958 | 0.4146 |
| 1.3003 | 15.0 | 90 | 1.3889 | 0.4146 |
| 1.3003 | 16.0 | 96 | 1.3827 | 0.4146 |
| 1.3072 | 17.0 | 102 | 1.3788 | 0.3902 |
| 1.3072 | 18.0 | 108 | 1.3733 | 0.4146 |
| 1.2978 | 19.0 | 114 | 1.3664 | 0.4390 |
| 1.268 | 20.0 | 120 | 1.3623 | 0.4390 |
| 1.268 | 21.0 | 126 | 1.3569 | 0.4390 |
| 1.265 | 22.0 | 132 | 1.3511 | 0.4390 |
| 1.265 | 23.0 | 138 | 1.3470 | 0.4634 |
| 1.2559 | 24.0 | 144 | 1.3424 | 0.4390 |
| 1.2443 | 25.0 | 150 | 1.3395 | 0.4146 |
| 1.2443 | 26.0 | 156 | 1.3357 | 0.4390 |
| 1.2468 | 27.0 | 162 | 1.3318 | 0.4390 |
| 1.2468 | 28.0 | 168 | 1.3281 | 0.4390 |
| 1.2381 | 29.0 | 174 | 1.3262 | 0.4390 |
| 1.2466 | 30.0 | 180 | 1.3249 | 0.4146 |
| 1.2466 | 31.0 | 186 | 1.3215 | 0.4390 |
| 1.234 | 32.0 | 192 | 1.3185 | 0.4390 |
| 1.234 | 33.0 | 198 | 1.3170 | 0.4390 |
| 1.2144 | 34.0 | 204 | 1.3158 | 0.4390 |
| 1.2407 | 35.0 | 210 | 1.3143 | 0.4390 |
| 1.2407 | 36.0 | 216 | 1.3132 | 0.4390 |
| 1.2238 | 37.0 | 222 | 1.3125 | 0.4390 |
| 1.2238 | 38.0 | 228 | 1.3116 | 0.4390 |
| 1.221 | 39.0 | 234 | 1.3110 | 0.4390 |
| 1.1985 | 40.0 | 240 | 1.3104 | 0.4390 |
| 1.1985 | 41.0 | 246 | 1.3101 | 0.4390 |
| 1.2078 | 42.0 | 252 | 1.3101 | 0.4390 |
| 1.2078 | 43.0 | 258 | 1.3101 | 0.4390 |
| 1.1965 | 44.0 | 264 | 1.3101 | 0.4390 |
| 1.2151 | 45.0 | 270 | 1.3101 | 0.4390 |
| 1.2151 | 46.0 | 276 | 1.3101 | 0.4390 |
| 1.2187 | 47.0 | 282 | 1.3101 | 0.4390 |
| 1.2187 | 48.0 | 288 | 1.3101 | 0.4390 |
| 1.1908 | 49.0 | 294 | 1.3101 | 0.4390 |
| 1.1985 | 50.0 | 300 | 1.3101 | 0.4390 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0