[mieb] Investigate voc2007 vlm2vec #1825
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isaac-chung
commented
Jan 16, 2025
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@gowitheflow-1998 I've left some notes below to supplement findings. It seems like when LoRA was run, samples_per_label might have been low, e.g. 8, instead of 64.
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| _unique_train_embeddings = normalize_embeddings_to_numpy( | ||
| model.get_image_embeddings( | ||
| unique_train_images, | ||
| **encode_kwargs, | ||
| ) |
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No change from adding normalize_embeddings_to_numpy. Will revert before merging.
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| X_test = normalize_embeddings_to_numpy( | ||
| model.get_image_embeddings(test_images, **encode_kwargs) | ||
| ) |
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same here, will revert this change.
| "languages": [ | ||
| "eng-Latn" | ||
| ], | ||
| "lrap": 0.7205710375157255, |
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Using commits to track lrap scores for both models at different samples_per_label. Will remove before merging.
| @@ -55,3 +55,5 @@ class VOC2007Classification(AbsTaskImageMultilabelClassification): | |||
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| # To be removed when we want full results | |||
| n_experiments: int = 5 | |||
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| samples_per_label: int = 64 | |||
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Fixes #1792
samples_per_labelsamples_per_label=64.Checklist
make test.make lint.