[multimodal] Upgrade preset and update the finetuning example for object detection #3262
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Job PR-3262-cf0f781 is done. |
zhiqiangdon
reviewed
Jun 6, 2023
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Why to change errors to warnings? Are there cases where class number or classes are missing but still work?
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Because in test_preset.py we did not provide sample_data_path and new DINO model does not have a default CLASSES value and the test will fail.
| if num_gpus is not None: | ||
| hyperparameters["env.num_gpus"] = num_gpus | ||
| if val_metric is not None: | ||
| hyperparameters["optimization.val_metric"] = val_metric |
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I can just remove the val_metric here. Later I'll test different val_metric's performance and add it back
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Job PR-3262-26f8ab2 is done. |
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For benchmarking result for three new presets, check internal quip document "Autogluon Object Detection Benchmarking in 0.8.0".
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