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keras-io/cifar10_metric_learning
cifar10_metric_learning is a image classification model from keras-io. Use it when you need a label for an image. It is set up for tf-keras.
Metric learning aims to measure the similarity among data samples and to learn embedding models. The motivation is to embed inputs in an embedding space such that similar images are close together in that space while…
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From the Hugging Face model README
Metric learning aims to measure the similarity among data samples and to learn embedding models. The motivation is to embed inputs in an embedding space such that similar images are close together in that space while dissimilar ones are far away.
The model in this repo is an example which demonstrates the capabilities of metric learning to create embeddings. These embeddings are then used to perform Image Similarity Search.
Full credits to Mat Kelcey for this work.
More information needed
Trained and evaluated on CIFAR-10 dataset.
| name | learning_rate | decay | beta_1 | beta_2 | epsilon | amsgrad | training_precision |
|---|---|---|---|---|---|---|---|
| Adam | 0.0010000000474974513 | 0.0 | 0.8999999761581421 | 0.9990000128746033 | 1e-07 | False | float32 |
| Epochs | Train Loss |
|---|---|
| 1 | 2.248 |
| 2 | 2.11 |
| 3 | 2.042 |
| 4 | 1.998 |
| 5 | 1.957 |
| 6 | 1.929 |
| 7 | 1.897 |
| 8 | 1.879 |
| 9 | 1.844 |
| 10 | 1.807 |
| 11 | 1.799 |
| 12 | 1.761 |
| 13 | 1.762 |
| 14 | 1.735 |
| 15 | 1.713 |
| 16 | 1.687 |
| 17 | 1.669 |
| 18 | 1.646 |
| 19 | 1.633 |
| 20 | 1.619 |
