Comments (2)
num positive matches 1416/2000
label distance
possible 0.0288222
likely 0.00458199
very_likely 0.000248671
match 0.0359477
distance f1 precision recall
0.000248671 0.309069 1 0.18
0.000498652 0.438326 0.99 0.28
0.00051856 0.451965 1 0.29
0.000980318 0.619186 0.99 0.45
0.00103468 0.630163 0.98 0.46
0.0010711 0.635407 0.99 0.47
0.00142562 0.709213 0.98 0.56
0.00171316 0.737118 0.97 0.6
0.00231791 0.769101 0.96 0.64
0.00234365 0.769296 0.95 0.64
0.00237638 0.771368 0.96 0.65
0.00276017 0.783292 0.95 0.67
0.0030542 0.793328 0.94 0.69
0.00326419 0.795491 0.93 0.7
0.00376821 0.804434 0.92 0.72
0.0042907 0.80984 0.91 0.73
0.0042969 0.809988 0.9 0.73
0.00431204 0.810452 0.91 0.73
0.00458175 0.810518 0.9 0.74
0.00458199 0.810205 0.89 0.74
0.00464582 0.812042 0.9 0.74
0.00505996 0.812834 0.89 0.75
0.00543237 0.81077 0.88 0.75
0.0059306 0.808431 0.87 0.76
0.00784302 0.815663 0.86 0.78
0.0100467 0.824593 0.85 0.81
0.0119423 0.826134 0.84 0.82
0.0134963 0.826516 0.83 0.83
0.0135162 0.826638 0.82 0.83
0.013761 0.827878 0.83 0.83
0.0138208 0.828411 0.82 0.83
0.0138208 0.828822 0.83 0.83
0.016178 0.83062 0.82 0.85
0.0184268 0.830253 0.81 0.86
0.0184957 0.829969 0.8 0.86
0.0185173 0.830769 0.81 0.86
0.0215253 0.831536 0.8 0.87
0.0288222 0.834051 0.79 0.89
0.0359477 0.837179 0.78 0.91
0.0404364 0.833815 0.77 0.92
0.0495148 0.836066 0.76 0.94
0.0576776 0.833385 0.75 0.94
0.0579422 0.833126 0.74 0.94
0.0599245 0.834318 0.75 0.95
0.0713266 0.832005 0.74 0.96
0.114868 0.832029 0.73 0.98
0.210144 0.830222 0.72 0.99
0.395062 0.82904 0.71 1
from similarity.
Still some issues with the calibration even after the rewerite.
from similarity.
Related Issues (20)
- What values of metrics can be interpreted as successful during training Similarity Models HOT 2
- [Typo] Lables instead of labels HOT 1
- self-supervised segmentation and detection
- VicReg implementation gives "nan" loss HOT 3
- Problem using the "brute_force" search method HOT 3
- README.md typo
- Out of memory error: Multi-GPUs not used when training semi-supervised model
- Error with multishotfilesampler HOT 4
- Race condition during EvalCallback HOT 1
- Add Colab example demonstrating multiple metrics in Callback.
- Replace all examples using MemorySamplers with the TFData_Samplers HOT 1
- Replace all examples using NMSLIB with KNNSearch HOT 1
- Add ConvNeXtSmall to architectures HOT 1
- Add warning / update to TF addon to help people transition
- Custom Architecture for Backbone model
- Update readme with v0.18 info
- TripletLoss will produce only NaN when using mixed bfloat16 precision
- tfa.losses.TripletSemiHardLoss() replacement? HOT 2
- Calculation of mean Averge Precision (mAP)
- Tensorflow > 2.11 ? HOT 3
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from similarity.