meat_calssify_fresh_crop_fixed_overlap_V_0_2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3158
- Accuracy: 0.9051
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 1
- 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 |
---|---|---|---|---|
1.0836 | 1.0 | 20 | 1.0836 | 0.3892 |
1.0325 | 2.0 | 40 | 1.0308 | 0.5032 |
0.9331 | 3.0 | 60 | 0.9478 | 0.5506 |
0.8711 | 4.0 | 80 | 0.9827 | 0.5380 |
0.8252 | 5.0 | 100 | 0.9171 | 0.5665 |
0.7597 | 6.0 | 120 | 0.8175 | 0.6234 |
0.6528 | 7.0 | 140 | 0.7884 | 0.6835 |
0.5646 | 8.0 | 160 | 0.7034 | 0.7025 |
0.5026 | 9.0 | 180 | 0.6805 | 0.7025 |
0.4534 | 10.0 | 200 | 0.6223 | 0.7690 |
0.4244 | 11.0 | 220 | 0.6262 | 0.7405 |
0.4077 | 12.0 | 240 | 0.6230 | 0.7595 |
0.3962 | 13.0 | 260 | 0.6731 | 0.7184 |
0.3587 | 14.0 | 280 | 0.5633 | 0.7911 |
0.316 | 15.0 | 300 | 0.5808 | 0.7848 |
0.2472 | 16.0 | 320 | 0.5478 | 0.7943 |
0.277 | 17.0 | 340 | 0.5609 | 0.8038 |
0.2586 | 18.0 | 360 | 0.5427 | 0.8133 |
0.2405 | 19.0 | 380 | 0.5207 | 0.8165 |
0.2141 | 20.0 | 400 | 0.4552 | 0.8323 |
0.2052 | 21.0 | 420 | 0.5201 | 0.8006 |
0.2182 | 22.0 | 440 | 0.3928 | 0.8544 |
0.1698 | 23.0 | 460 | 0.4459 | 0.8449 |
0.1618 | 24.0 | 480 | 0.4502 | 0.8323 |
0.1915 | 25.0 | 500 | 0.4057 | 0.8703 |
0.1596 | 26.0 | 520 | 0.4650 | 0.8386 |
0.1446 | 27.0 | 540 | 0.3713 | 0.8766 |
0.17 | 28.0 | 560 | 0.4394 | 0.8544 |
0.141 | 29.0 | 580 | 0.5494 | 0.8196 |
0.1563 | 30.0 | 600 | 0.5431 | 0.8196 |
0.1216 | 31.0 | 620 | 0.5010 | 0.8481 |
0.1081 | 32.0 | 640 | 0.4454 | 0.8608 |
0.1205 | 33.0 | 660 | 0.4664 | 0.8418 |
0.1325 | 34.0 | 680 | 0.4690 | 0.8481 |
0.1152 | 35.0 | 700 | 0.3433 | 0.9019 |
0.1218 | 36.0 | 720 | 0.4063 | 0.8671 |
0.1163 | 37.0 | 740 | 0.3552 | 0.8861 |
0.0976 | 38.0 | 760 | 0.4137 | 0.8734 |
0.1163 | 39.0 | 780 | 0.4193 | 0.8797 |
0.1034 | 40.0 | 800 | 0.3740 | 0.8892 |
0.1033 | 41.0 | 820 | 0.4036 | 0.8671 |
0.0806 | 42.0 | 840 | 0.4396 | 0.8639 |
0.0764 | 43.0 | 860 | 0.4137 | 0.8608 |
0.0955 | 44.0 | 880 | 0.4019 | 0.8734 |
0.0768 | 45.0 | 900 | 0.3778 | 0.8829 |
0.0824 | 46.0 | 920 | 0.3930 | 0.8829 |
0.0837 | 47.0 | 940 | 0.3524 | 0.8924 |
0.0817 | 48.0 | 960 | 0.3113 | 0.9177 |
0.0767 | 49.0 | 980 | 0.3881 | 0.8797 |
0.0769 | 50.0 | 1000 | 0.3158 | 0.9051 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for talli96123/meat_calssify_fresh_crop_fixed_overlap_V_0_2
Base model
google/vit-base-patch16-224-in21k
Finetuned
this model