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_rms_001_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: 0.4222222222222222
hushem_1x_beit_base_rms_001_fold1
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: 1.6554
- Accuracy: 0.4222
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 | 4.7780 | 0.2444 |
| 5.2713 | 2.0 | 12 | 1.6054 | 0.2444 |
| 5.2713 | 3.0 | 18 | 1.4082 | 0.2444 |
| 1.584 | 4.0 | 24 | 1.4460 | 0.2444 |
| 1.4611 | 5.0 | 30 | 1.3995 | 0.2444 |
| 1.4611 | 6.0 | 36 | 1.4702 | 0.2444 |
| 1.426 | 7.0 | 42 | 1.4146 | 0.2889 |
| 1.426 | 8.0 | 48 | 1.4135 | 0.2667 |
| 1.4231 | 9.0 | 54 | 1.3923 | 0.2444 |
| 1.3996 | 10.0 | 60 | 1.3952 | 0.3333 |
| 1.3996 | 11.0 | 66 | 1.3447 | 0.3111 |
| 1.3678 | 12.0 | 72 | 1.2012 | 0.4667 |
| 1.3678 | 13.0 | 78 | 1.2676 | 0.3111 |
| 1.3823 | 14.0 | 84 | 1.6735 | 0.2444 |
| 1.3117 | 15.0 | 90 | 1.4063 | 0.2889 |
| 1.3117 | 16.0 | 96 | 1.1481 | 0.5111 |
| 1.2447 | 17.0 | 102 | 1.1199 | 0.4444 |
| 1.2447 | 18.0 | 108 | 1.4527 | 0.3556 |
| 1.159 | 19.0 | 114 | 1.2632 | 0.4 |
| 1.1248 | 20.0 | 120 | 1.8823 | 0.3111 |
| 1.1248 | 21.0 | 126 | 1.3002 | 0.3556 |
| 1.076 | 22.0 | 132 | 1.3851 | 0.3333 |
| 1.076 | 23.0 | 138 | 1.5013 | 0.4444 |
| 1.017 | 24.0 | 144 | 1.6658 | 0.3556 |
| 1.0181 | 25.0 | 150 | 1.6317 | 0.3556 |
| 1.0181 | 26.0 | 156 | 2.0640 | 0.3556 |
| 0.9565 | 27.0 | 162 | 1.8453 | 0.3778 |
| 0.9565 | 28.0 | 168 | 1.5546 | 0.3556 |
| 0.9059 | 29.0 | 174 | 1.7001 | 0.4222 |
| 0.8651 | 30.0 | 180 | 1.6735 | 0.4444 |
| 0.8651 | 31.0 | 186 | 1.6947 | 0.4667 |
| 0.8326 | 32.0 | 192 | 1.8722 | 0.3333 |
| 0.8326 | 33.0 | 198 | 1.5166 | 0.4667 |
| 0.7811 | 34.0 | 204 | 1.5728 | 0.4222 |
| 0.7343 | 35.0 | 210 | 1.5820 | 0.4444 |
| 0.7343 | 36.0 | 216 | 1.5827 | 0.4444 |
| 0.7013 | 37.0 | 222 | 1.8267 | 0.4 |
| 0.7013 | 38.0 | 228 | 1.7339 | 0.3778 |
| 0.6091 | 39.0 | 234 | 1.6279 | 0.4222 |
| 0.6541 | 40.0 | 240 | 1.6395 | 0.4444 |
| 0.6541 | 41.0 | 246 | 1.6688 | 0.4 |
| 0.5842 | 42.0 | 252 | 1.6554 | 0.4222 |
| 0.5842 | 43.0 | 258 | 1.6554 | 0.4222 |
| 0.591 | 44.0 | 264 | 1.6554 | 0.4222 |
| 0.5639 | 45.0 | 270 | 1.6554 | 0.4222 |
| 0.5639 | 46.0 | 276 | 1.6554 | 0.4222 |
| 0.5746 | 47.0 | 282 | 1.6554 | 0.4222 |
| 0.5746 | 48.0 | 288 | 1.6554 | 0.4222 |
| 0.5561 | 49.0 | 294 | 1.6554 | 0.4222 |
| 0.5875 | 50.0 | 300 | 1.6554 | 0.4222 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0