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README.md
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@@ -37,12 +37,8 @@ The linear modules **albert.encoder.albert_layer_groups.0.albert_layers.0.ffn_ou
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### Test result
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- Batch size = 8
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- [Amazon Web Services](https://aws.amazon.com/) c6i.xlarge (Intel ICE Lake: 4 vCPUs, 8g Memory) instance.
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| |INT8|FP32|
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|---|:---:|:---:|
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| **Throughput (samples/sec)** |13.464|11.854|
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| **Accuracy (eval-accuracy)** |0.9255|0.9232|
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| **Model size (MB)** |25|44.6|
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@@ -54,7 +50,3 @@ int8_model = OptimizedModel.from_pretrained(
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'Intel/albert-base-v2-sst2-int8-static',
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)
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```
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Notes:
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- The INT8 model has better performance than the FP32 model when the CPU is fully occupied. Otherwise, there will be the illusion that INT8 is inferior to FP32.
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### Test result
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| |INT8|FP32|
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|---|:---:|:---:|
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| **Accuracy (eval-accuracy)** |0.9255|0.9232|
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| **Model size (MB)** |25|44.6|
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'Intel/albert-base-v2-sst2-int8-static',
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)
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```
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