hushem_1x_beit_base_rms_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: 3.2977
- Accuracy: 0.5
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 | 1.3978 | 0.2619 |
1.9888 | 2.0 | 12 | 1.3961 | 0.2381 |
1.9888 | 3.0 | 18 | 1.3839 | 0.2619 |
1.4109 | 4.0 | 24 | 1.3035 | 0.3095 |
1.3832 | 5.0 | 30 | 1.2707 | 0.5714 |
1.3832 | 6.0 | 36 | 1.2845 | 0.3571 |
1.4922 | 7.0 | 42 | 1.4385 | 0.2857 |
1.4922 | 8.0 | 48 | 1.2908 | 0.2619 |
1.2776 | 9.0 | 54 | 1.3088 | 0.5238 |
1.269 | 10.0 | 60 | 1.2412 | 0.3333 |
1.269 | 11.0 | 66 | 1.1676 | 0.5238 |
1.2132 | 12.0 | 72 | 1.1566 | 0.4286 |
1.2132 | 13.0 | 78 | 1.0746 | 0.5714 |
1.115 | 14.0 | 84 | 1.2329 | 0.4286 |
1.1413 | 15.0 | 90 | 1.1499 | 0.4048 |
1.1413 | 16.0 | 96 | 1.0494 | 0.5476 |
0.9563 | 17.0 | 102 | 0.9577 | 0.5238 |
0.9563 | 18.0 | 108 | 1.2486 | 0.4048 |
0.9343 | 19.0 | 114 | 1.2396 | 0.5238 |
0.8964 | 20.0 | 120 | 1.5448 | 0.3810 |
0.8964 | 21.0 | 126 | 1.6028 | 0.4762 |
0.826 | 22.0 | 132 | 1.0756 | 0.5714 |
0.826 | 23.0 | 138 | 1.4576 | 0.4048 |
0.6612 | 24.0 | 144 | 1.5635 | 0.4286 |
0.7361 | 25.0 | 150 | 1.2476 | 0.5952 |
0.7361 | 26.0 | 156 | 1.6591 | 0.4048 |
0.5674 | 27.0 | 162 | 1.5837 | 0.5238 |
0.5674 | 28.0 | 168 | 2.8490 | 0.4286 |
0.5637 | 29.0 | 174 | 1.9394 | 0.5714 |
0.4528 | 30.0 | 180 | 2.5319 | 0.4762 |
0.4528 | 31.0 | 186 | 1.8994 | 0.5714 |
0.455 | 32.0 | 192 | 2.3813 | 0.5476 |
0.455 | 33.0 | 198 | 2.3989 | 0.5 |
0.4317 | 34.0 | 204 | 2.5912 | 0.5 |
0.3921 | 35.0 | 210 | 2.8985 | 0.4762 |
0.3921 | 36.0 | 216 | 2.9682 | 0.5 |
0.3189 | 37.0 | 222 | 3.2291 | 0.5 |
0.3189 | 38.0 | 228 | 3.0818 | 0.5476 |
0.3067 | 39.0 | 234 | 3.1819 | 0.5238 |
0.2523 | 40.0 | 240 | 3.2200 | 0.4524 |
0.2523 | 41.0 | 246 | 3.2572 | 0.5 |
0.2633 | 42.0 | 252 | 3.2977 | 0.5 |
0.2633 | 43.0 | 258 | 3.2977 | 0.5 |
0.2304 | 44.0 | 264 | 3.2977 | 0.5 |
0.2585 | 45.0 | 270 | 3.2977 | 0.5 |
0.2585 | 46.0 | 276 | 3.2977 | 0.5 |
0.2417 | 47.0 | 282 | 3.2977 | 0.5 |
0.2417 | 48.0 | 288 | 3.2977 | 0.5 |
0.2307 | 49.0 | 294 | 3.2977 | 0.5 |
0.2495 | 50.0 | 300 | 3.2977 | 0.5 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
microsoft/beit-base-patch16-224