yapwithai
/

phone-screen-classifier

@@ -39,7 +39,6 @@ This model is built for routing and filtering mobile screenshot workflows. It se
 | :------------------------ | :------------------------------------------------------------- |
 | `onnx/model.onnx`         | ONNX model for CPU/server inference.                           |
 | `onnx/model.fp16.onnx`    | Optional FP16 ONNX candidate.                                  |
-| `onnx/model.int8.onnx`    | Optional INT8 ONNX candidate.                                  |
 | `onnx/model.onnx.data`    | External ONNX weight data loaded beside `model.onnx`.          |
 | `model.safetensors`       | PyTorch state dict for reproducibility and continued training. |
 | `config.json`             | Model identity, base model, output names, and label arrays.    |
@@ -77,12 +76,6 @@ Inference uses `argmax` for both heads in this version.
 | fp16 | screen-balanced test | safety | 0.9776 | 0.9285 | 0.9110 | 0.9978 | 6246 |
 | fp16 | safety-balanced test | screen | 0.9580 | 0.7752 | 0.6547 | 0.9870 | 3000 |
 | fp16 | safety-balanced test | safety | 0.8957 | 0.8957 | 0.8947 | 0.9847 | 3000 |
-| int8 | full test | screen | 0.0018 | 0.0424 | 0.0024 | 0.0278 | 23615 |
-| int8 | full test | safety | 0.1013 | 0.3502 | 0.0696 | 0.9431 | 23615 |
-| int8 | screen-balanced test | screen | 0.0062 | 0.0424 | 0.0031 | 0.1039 | 6246 |
-| int8 | screen-balanced test | safety | 0.1703 | 0.3686 | 0.1153 | 0.9241 | 6246 |
-| int8 | safety-balanced test | screen | 0.0003 | 0.0417 | 0.0000 | 0.0140 | 3000 |
-| int8 | safety-balanced test | safety | 0.3493 | 0.3493 | 0.1992 | 0.6667 | 3000 |
 ## CPU Timing
@@ -90,7 +83,6 @@ Inference uses `argmax` for both heads in this version.
 | :-- | --: | --: | --: | --: | --: | --: | --: |
 | fp32 | 20.0538 | 0.12 ms | 49.52 ms | 49.87 ms | 57.84 ms | 85.82 ms | onnxruntime:CPUExecutionProvider |
 | fp16 | 20.8351 | 0.11 ms | 47.69 ms | 48.00 ms | 48.60 ms | 63.65 ms | onnxruntime:CPUExecutionProvider |
-| int8 | 72.6504 | 0.14 ms | 13.36 ms | 13.76 ms | 14.07 ms | 18.01 ms | onnxruntime:CPUExecutionProvider |
 Timing is measured with ONNX Runtime CPU execution on `Apple M4 Max (16 logical cores)`. Total latency includes image load/preprocess, model inference, and label decoding.

 | :------------------------ | :------------------------------------------------------------- |
 | `onnx/model.onnx`         | ONNX model for CPU/server inference.                           |
 | `onnx/model.fp16.onnx`    | Optional FP16 ONNX candidate.                                  |
 | `onnx/model.onnx.data`    | External ONNX weight data loaded beside `model.onnx`.          |
 | `model.safetensors`       | PyTorch state dict for reproducibility and continued training. |
 | `config.json`             | Model identity, base model, output names, and label arrays.    |
 | fp16 | screen-balanced test | safety | 0.9776 | 0.9285 | 0.9110 | 0.9978 | 6246 |
 | fp16 | safety-balanced test | screen | 0.9580 | 0.7752 | 0.6547 | 0.9870 | 3000 |
 | fp16 | safety-balanced test | safety | 0.8957 | 0.8957 | 0.8947 | 0.9847 | 3000 |
 ## CPU Timing
 | :-- | --: | --: | --: | --: | --: | --: | --: |
 | fp32 | 20.0538 | 0.12 ms | 49.52 ms | 49.87 ms | 57.84 ms | 85.82 ms | onnxruntime:CPUExecutionProvider |
 | fp16 | 20.8351 | 0.11 ms | 47.69 ms | 48.00 ms | 48.60 ms | 63.65 ms | onnxruntime:CPUExecutionProvider |
 Timing is measured with ONNX Runtime CPU execution on `Apple M4 Max (16 logical cores)`. Total latency includes image load/preprocess, model inference, and label decoding.

onnx/model.int8.onnx DELETED Viewed

@@ -1,3 +0,0 @@
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