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Manuappu5670
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mobilevit-xx-small-finetuned-eurosat

Safetensors
mobilevit
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1491
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- - Accuracy: 0.636
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  ## Model description
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@@ -46,42 +46,59 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 30
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 4 | 2.2718 | 0.212 |
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- | No log | 2.0 | 8 | 2.1032 | 0.29 |
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- | 2.1883 | 3.0 | 12 | 1.9200 | 0.336 |
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- | 2.1883 | 4.0 | 16 | 2.7332 | 0.26 |
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- | 1.7537 | 5.0 | 20 | 2.0565 | 0.354 |
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- | 1.7537 | 6.0 | 24 | 1.9996 | 0.352 |
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- | 1.7537 | 7.0 | 28 | 1.7919 | 0.388 |
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- | 1.525 | 8.0 | 32 | 1.9682 | 0.366 |
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- | 1.525 | 9.0 | 36 | 1.5504 | 0.44 |
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- | 1.41 | 10.0 | 40 | 1.6390 | 0.406 |
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- | 1.41 | 11.0 | 44 | 1.8055 | 0.482 |
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- | 1.41 | 12.0 | 48 | 1.8536 | 0.372 |
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- | 1.2638 | 13.0 | 52 | 1.6080 | 0.488 |
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- | 1.2638 | 14.0 | 56 | 1.8101 | 0.418 |
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- | 1.1194 | 15.0 | 60 | 1.7426 | 0.422 |
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- | 1.1194 | 16.0 | 64 | 1.7981 | 0.452 |
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- | 1.1194 | 17.0 | 68 | 2.0886 | 0.392 |
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- | 1.0082 | 18.0 | 72 | 1.4252 | 0.538 |
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- | 1.0082 | 19.0 | 76 | 1.3338 | 0.576 |
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- | 0.9556 | 20.0 | 80 | 1.7173 | 0.492 |
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- | 0.9556 | 21.0 | 84 | 1.4067 | 0.572 |
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- | 0.9556 | 22.0 | 88 | 1.1839 | 0.614 |
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- | 0.8404 | 23.0 | 92 | 1.2037 | 0.612 |
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- | 0.8404 | 24.0 | 96 | 1.4832 | 0.552 |
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- | 0.7603 | 25.0 | 100 | 1.3205 | 0.592 |
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- | 0.7603 | 26.0 | 104 | 1.2505 | 0.61 |
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- | 0.7603 | 27.0 | 108 | 1.2412 | 0.622 |
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- | 0.7096 | 28.0 | 112 | 1.1740 | 0.626 |
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- | 0.7096 | 29.0 | 116 | 1.1465 | 0.624 |
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- | 0.6157 | 30.0 | 120 | 1.1491 | 0.636 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0688
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+ - Accuracy: 0.64
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 50
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9231 | 3 | 2.2814 | 0.11 |
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+ | No log | 1.8462 | 6 | 2.2279 | 0.26 |
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+ | No log | 2.7692 | 9 | 2.1060 | 0.29 |
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+ | 2.2256 | 4.0 | 13 | 1.8601 | 0.31 |
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+ | 2.2256 | 4.9231 | 16 | 1.8917 | 0.32 |
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+ | 2.2256 | 5.8462 | 19 | 1.7590 | 0.33 |
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+ | 1.8 | 6.7692 | 22 | 2.9505 | 0.21 |
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+ | 1.8 | 8.0 | 26 | 2.4407 | 0.19 |
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+ | 1.8 | 8.9231 | 29 | 2.6913 | 0.36 |
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+ | 1.6404 | 9.8462 | 32 | 1.4094 | 0.48 |
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+ | 1.6404 | 10.7692 | 35 | 1.4011 | 0.47 |
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+ | 1.6404 | 12.0 | 39 | 1.7594 | 0.45 |
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+ | 1.4817 | 12.9231 | 42 | 1.4313 | 0.46 |
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+ | 1.4817 | 13.8462 | 45 | 1.2744 | 0.49 |
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+ | 1.4817 | 14.7692 | 48 | 1.4527 | 0.46 |
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+ | 1.2872 | 16.0 | 52 | 1.5522 | 0.42 |
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+ | 1.2872 | 16.9231 | 55 | 1.7600 | 0.38 |
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+ | 1.2872 | 17.8462 | 58 | 1.3952 | 0.53 |
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+ | 1.2307 | 18.7692 | 61 | 1.5067 | 0.51 |
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+ | 1.2307 | 20.0 | 65 | 1.6311 | 0.51 |
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+ | 1.2307 | 20.9231 | 68 | 1.3987 | 0.58 |
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+ | 1.0604 | 21.8462 | 71 | 1.4128 | 0.54 |
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+ | 1.0604 | 22.7692 | 74 | 1.1939 | 0.56 |
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+ | 1.0604 | 24.0 | 78 | 1.4324 | 0.49 |
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+ | 1.0053 | 24.9231 | 81 | 1.3661 | 0.53 |
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+ | 1.0053 | 25.8462 | 84 | 1.2528 | 0.53 |
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+ | 1.0053 | 26.7692 | 87 | 1.2040 | 0.57 |
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+ | 0.8327 | 28.0 | 91 | 1.1886 | 0.61 |
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+ | 0.8327 | 28.9231 | 94 | 1.0321 | 0.66 |
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+ | 0.8327 | 29.8462 | 97 | 1.1496 | 0.61 |
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+ | 0.7456 | 30.7692 | 100 | 1.1801 | 0.61 |
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+ | 0.7456 | 32.0 | 104 | 1.2886 | 0.53 |
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+ | 0.7456 | 32.9231 | 107 | 1.2215 | 0.6 |
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+ | 0.7106 | 33.8462 | 110 | 1.2372 | 0.55 |
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+ | 0.7106 | 34.7692 | 113 | 1.1834 | 0.62 |
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+ | 0.7106 | 36.0 | 117 | 1.2001 | 0.64 |
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+ | 0.5914 | 36.9231 | 120 | 1.1182 | 0.63 |
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+ | 0.5914 | 37.8462 | 123 | 1.2223 | 0.62 |
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+ | 0.5914 | 38.7692 | 126 | 1.2443 | 0.59 |
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+ | 0.5601 | 40.0 | 130 | 1.2605 | 0.59 |
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+ | 0.5601 | 40.9231 | 133 | 1.2940 | 0.6 |
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+ | 0.5601 | 41.8462 | 136 | 1.2284 | 0.59 |
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+ | 0.5601 | 42.7692 | 139 | 1.1884 | 0.61 |
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+ | 0.5151 | 44.0 | 143 | 1.1789 | 0.63 |
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+ | 0.5151 | 44.9231 | 146 | 1.1297 | 0.62 |
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+ | 0.5151 | 45.8462 | 149 | 1.0879 | 0.63 |
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+ | 0.4531 | 46.1538 | 150 | 1.0688 | 0.64 |
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  ### Framework versions
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