SmilingWolf
commited on
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Parent(s):
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Update model files
Browse files- README.md +15 -2
- model.msgpack +1 -1
- model.onnx +1 -1
- model.safetensors +1 -1
- sw_jax_cv_config.json +1 -1
README.md
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Tags with less than 600 images were filtered out.
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## Validation results
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`P=R: threshold = 0.
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## What's new
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Model v1.1/Dataset v3:
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Amended the JAX model config file: add image size.
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No change to the trained weights.
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Model v1.0/Dataset v3:
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The batch dimension of the ONNX model is not fixed to 1 anymore. Now you can go crazy with batch inference.
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Switched to Macro-F1 to measure model performance since it gives me a better gauge of overall training progress.
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## Final words
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Subject to change and updates.
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Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.
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Tags with less than 600 images were filtered out.
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## Validation results
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`v2.0: P=R: threshold = 0.2682, F1 = 0.4419`
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`v1.0: P=R: threshold = 0.2570, F1 = 0.4282`
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## What's new
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Model v2.0/Dataset v3:
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Trained for a few more epochs.
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Used tag frequency-based loss scaling to combat class imbalance.
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Model v1.1/Dataset v3:
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Amended the JAX model config file: add image size.
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No change to the trained weights.
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Model v1.0/Dataset v3:
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The batch dimension of the ONNX model is not fixed to 1 anymore. Now you can go crazy with batch inference.
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Switched to Macro-F1 to measure model performance since it gives me a better gauge of overall training progress.
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# Runtime deps
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ONNX model requires `onnxruntime >= 1.17.0`
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# Inference code examples
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For timm: https://github.com/neggles/wdv3-timm
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For ONNX: https://huggingface.co/spaces/SmilingWolf/wd-tagger
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For JAX: https://github.com/SmilingWolf/wdv3-jax
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## Final words
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Subject to change and updates.
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Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.
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model.msgpack
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version https://git-lfs.github.com/spec/v1
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model.onnx
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@@ -1,3 +1,3 @@
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model.safetensors
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@@ -1,3 +1,3 @@
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sw_jax_cv_config.json
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"use_conv_bias": true,
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"layer_norm_eps": 1e-06
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}
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}
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"use_conv_bias": true,
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"layer_norm_eps": 1e-06
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}
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}
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