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all-observation-type

Image Classification
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Safetensors
vit
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  1. README.md +37 -72
  2. model.safetensors +1 -1
  3. runs/May15_06-20-17_ab91efe686de/events.out.tfevents.1715754018.ab91efe686de.94836.23 +2 -2
README.md CHANGED
@@ -2,7 +2,6 @@
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  license: apache-2.0
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
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- - image-classification
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  - generated_from_trainer
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  metrics:
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  - f1
@@ -16,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # all-observation-type
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- This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the all-multi-class dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0073
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- - F1: 0.1819
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  ## Model description
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@@ -51,74 +50,40 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|
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- | 0.007 | 0.5814 | 100 | 0.0086 | 0.0448 |
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- | 0.0046 | 1.1628 | 200 | 0.0079 | 0.1397 |
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- | 0.0047 | 1.7442 | 300 | 0.0075 | 0.1034 |
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- | 0.0032 | 2.3256 | 400 | 0.0073 | 0.1819 |
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- | 0.0038 | 2.9070 | 500 | 0.0079 | 0.1638 |
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- | 0.0036 | 3.4884 | 600 | 0.0075 | 0.1789 |
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- | 0.0024 | 4.0698 | 700 | 0.0076 | 0.2093 |
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- | 0.0025 | 4.6512 | 800 | 0.0078 | 0.2001 |
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- | 0.0021 | 5.2326 | 900 | 0.0083 | 0.2238 |
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- | 0.0019 | 5.8140 | 1000 | 0.0083 | 0.2143 |
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- | 0.0017 | 6.3953 | 1100 | 0.0083 | 0.2113 |
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- | 0.002 | 6.9767 | 1200 | 0.0086 | 0.2316 |
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- | 0.0013 | 7.5581 | 1300 | 0.0087 | 0.2231 |
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- | 0.001 | 8.1395 | 1400 | 0.0085 | 0.2700 |
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- | 0.0013 | 8.7209 | 1500 | 0.0083 | 0.2882 |
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- | 0.0008 | 9.3023 | 1600 | 0.0094 | 0.2671 |
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- | 0.0011 | 9.8837 | 1700 | 0.0089 | 0.2583 |
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- | 0.0006 | 10.4651 | 1800 | 0.0099 | 0.2261 |
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- | 0.0005 | 11.0465 | 1900 | 0.0092 | 0.2654 |
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- | 0.0005 | 11.6279 | 2000 | 0.0099 | 0.2014 |
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- | 0.0004 | 12.2093 | 2100 | 0.0099 | 0.2383 |
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- | 0.0003 | 12.7907 | 2200 | 0.0101 | 0.2587 |
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- | 0.0003 | 13.3721 | 2300 | 0.0103 | 0.2541 |
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- | 0.0002 | 13.9535 | 2400 | 0.0106 | 0.2474 |
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- | 0.0002 | 14.5349 | 2500 | 0.0108 | 0.2535 |
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- | 0.0001 | 15.1163 | 2600 | 0.0109 | 0.2531 |
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- | 0.0002 | 15.6977 | 2700 | 0.0110 | 0.2522 |
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- | 0.0001 | 16.2791 | 2800 | 0.0112 | 0.2647 |
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- | 0.0001 | 16.8605 | 2900 | 0.0115 | 0.2604 |
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- | 0.0001 | 17.4419 | 3000 | 0.0116 | 0.2642 |
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- | 0.0001 | 18.0233 | 3100 | 0.0119 | 0.2625 |
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- | 0.0001 | 18.6047 | 3200 | 0.0119 | 0.2715 |
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- | 0.0001 | 19.1860 | 3300 | 0.0120 | 0.2774 |
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- | 0.0001 | 19.7674 | 3400 | 0.0121 | 0.2887 |
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- | 0.0001 | 20.3488 | 3500 | 0.0123 | 0.2832 |
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- | 0.0001 | 20.9302 | 3600 | 0.0124 | 0.2692 |
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- | 0.0001 | 21.5116 | 3700 | 0.0125 | 0.2760 |
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- | 0.0001 | 22.0930 | 3800 | 0.0126 | 0.2694 |
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- | 0.0 | 22.6744 | 3900 | 0.0127 | 0.2717 |
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- | 0.0001 | 23.2558 | 4000 | 0.0128 | 0.2657 |
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- | 0.0 | 23.8372 | 4100 | 0.0129 | 0.2852 |
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- | 0.0001 | 24.4186 | 4200 | 0.0130 | 0.2783 |
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- | 0.0001 | 25.0 | 4300 | 0.0130 | 0.2898 |
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- | 0.0 | 25.5814 | 4400 | 0.0131 | 0.2864 |
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- | 0.0 | 26.1628 | 4500 | 0.0132 | 0.2862 |
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- | 0.0001 | 26.7442 | 4600 | 0.0133 | 0.2965 |
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- | 0.0 | 27.3256 | 4700 | 0.0134 | 0.2921 |
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- | 0.0 | 27.9070 | 4800 | 0.0134 | 0.2841 |
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- | 0.0 | 28.4884 | 4900 | 0.0135 | 0.2896 |
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- | 0.0001 | 29.0698 | 5000 | 0.0136 | 0.2829 |
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- | 0.0001 | 29.6512 | 5100 | 0.0136 | 0.2864 |
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- | 0.0 | 30.2326 | 5200 | 0.0137 | 0.2898 |
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- | 0.0 | 30.8140 | 5300 | 0.0138 | 0.2878 |
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- | 0.0 | 31.3953 | 5400 | 0.0138 | 0.2829 |
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- | 0.0 | 31.9767 | 5500 | 0.0139 | 0.2910 |
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- | 0.0 | 32.5581 | 5600 | 0.0139 | 0.2910 |
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- | 0.0 | 33.1395 | 5700 | 0.0140 | 0.2864 |
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- | 0.0 | 33.7209 | 5800 | 0.0140 | 0.2910 |
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- | 0.0 | 34.3023 | 5900 | 0.0140 | 0.2910 |
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- | 0.0001 | 34.8837 | 6000 | 0.0141 | 0.2910 |
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- | 0.0 | 35.4651 | 6100 | 0.0141 | 0.2910 |
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- | 0.0 | 36.0465 | 6200 | 0.0142 | 0.2910 |
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- | 0.0 | 36.6279 | 6300 | 0.0142 | 0.2910 |
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- | 0.0 | 37.2093 | 6400 | 0.0142 | 0.2910 |
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- | 0.0 | 37.7907 | 6500 | 0.0142 | 0.2910 |
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- | 0.0001 | 38.3721 | 6600 | 0.0142 | 0.2910 |
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- | 0.0 | 38.9535 | 6700 | 0.0143 | 0.2910 |
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- | 0.0 | 39.5349 | 6800 | 0.0143 | 0.2910 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
 
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  - generated_from_trainer
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  metrics:
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  - f1
 
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  # all-observation-type
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0082
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+ - F1: 0.1324
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|
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+ | 0.0726 | 1.1628 | 100 | 0.0660 | 0.0 |
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+ | 0.0264 | 2.3256 | 200 | 0.0247 | 0.0 |
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+ | 0.0161 | 3.4884 | 300 | 0.0165 | 0.0 |
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+ | 0.0133 | 4.6512 | 400 | 0.0135 | 0.0 |
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+ | 0.0124 | 5.8140 | 500 | 0.0120 | 0.0 |
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+ | 0.011 | 6.9767 | 600 | 0.0112 | 0.0 |
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+ | 0.0114 | 8.1395 | 700 | 0.0107 | 0.0 |
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+ | 0.0109 | 9.3023 | 800 | 0.0103 | 0.0 |
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+ | 0.0096 | 10.4651 | 900 | 0.0102 | 0.0 |
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+ | 0.0099 | 11.6279 | 1000 | 0.0098 | 0.0 |
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+ | 0.0089 | 12.7907 | 1100 | 0.0094 | 0.0 |
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+ | 0.0091 | 13.9535 | 1200 | 0.0093 | 0.0 |
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+ | 0.0081 | 15.1163 | 1300 | 0.0089 | 0.0 |
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+ | 0.0073 | 16.2791 | 1400 | 0.0089 | 0.0 |
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+ | 0.0071 | 17.4419 | 1500 | 0.0085 | 0.0 |
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+ | 0.0068 | 18.6047 | 1600 | 0.0082 | 0.0183 |
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+ | 0.0064 | 19.7674 | 1700 | 0.0082 | 0.0365 |
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+ | 0.0061 | 20.9302 | 1800 | 0.0086 | 0.0091 |
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+ | 0.0054 | 22.0930 | 1900 | 0.0082 | 0.0594 |
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+ | 0.0051 | 23.2558 | 2000 | 0.0080 | 0.0502 |
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+ | 0.0048 | 24.4186 | 2100 | 0.0079 | 0.0639 |
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+ | 0.0045 | 25.5814 | 2200 | 0.0080 | 0.0639 |
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+ | 0.0036 | 26.7442 | 2300 | 0.0079 | 0.1027 |
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+ | 0.0038 | 27.9070 | 2400 | 0.0079 | 0.1027 |
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+ | 0.0032 | 29.0698 | 2500 | 0.0077 | 0.0913 |
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+ | 0.004 | 30.2326 | 2600 | 0.0079 | 0.1027 |
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+ | 0.003 | 31.3953 | 2700 | 0.0081 | 0.0936 |
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+ | 0.0029 | 32.5581 | 2800 | 0.0080 | 0.0890 |
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+ | 0.0033 | 33.7209 | 2900 | 0.0081 | 0.0845 |
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+ | 0.0029 | 34.8837 | 3000 | 0.0081 | 0.1256 |
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+ | 0.0025 | 36.0465 | 3100 | 0.0081 | 0.1347 |
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+ | 0.0027 | 37.2093 | 3200 | 0.0081 | 0.1324 |
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+ | 0.0028 | 38.3721 | 3300 | 0.0082 | 0.1324 |
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+ | 0.0023 | 39.5349 | 3400 | 0.0082 | 0.1324 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  size 345933956
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