zhouyaqiang
5 years ago
1 changed files with 14 additions and 12 deletions
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model_zoo/official/cv/inceptionv3/README.md
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| @@ -35,7 +35,7 @@ The overall network architecture of InceptionV3 is show below: | |||
| Dataset used can refer to paper. | |||
| - Dataset size: ~125G, 1.2W colorful images in 1000 classes | |||
| - Dataset size: 125G, 1250k colorful images in 1000 classes | |||
| - Train: 120G, 1200k images | |||
| - Test: 5G, 50k images | |||
| - Data format: RGB images. | |||
| @@ -217,19 +217,21 @@ metric: {'Loss': 1.778, 'Top1-Acc':0.788, 'Top5-Acc':0.942} | |||
| ### Training Performance | |||
| | Parameters | InceptionV3 | | | |||
| | Parameters | Ascend | GPU | | |||
| | -------------------------- | ---------------------------------------------- | ------------------------- | | |||
| | Model Version | V1 | V1 | | |||
| | Model Version | InceptionV3 | InceptionV3 | | |||
| | Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G | NV SMI V100-16G(PCIE),cpu:2.10GHz 96cores, memory:250G | | |||
| | uploaded Date | 08/21/2020 | 08/21/2020 | | |||
| | MindSpore Version | 0.6.0-beta | 0.6.0-beta | | |||
| | Dataset | 1200k images | 1200k images | | |||
| | Batch_size | 128 | 128 | | |||
| | Training Parameters | src/config.py | src/config.py | | |||
| | Optimizer | RMSProp | RMSProp | | |||
| | Loss Function | SoftmaxCrossEntropy | SoftmaxCrossEntropy | | |||
| | outputs | probability | probability | | |||
| | Outputs | probability | probability | | |||
| | Loss | 1.98 | 1.98 | | |||
| | Accuracy (8p) | ACC1[78.8%] ACC5[94.2%] | ACC1[78.7%] ACC5[94.1%] | | |||
| | Total time (8p) | 11h | 72h | | |||
| | Accuracy (8p) | ACC1[78.8%] ACC5[94.2%] | ACC1[78.7%] ACC5[94.1%] | | |||
| | Total time (8p) | 11h | 72h | | |||
| | Params (M) | 103M | 103M | | |||
| | Checkpoint for Fine tuning | 313M | 312M | | |||
| | Scripts | [inceptionv3 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) | [inceptionv3 script](https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/inceptionv3) | | |||
| @@ -237,15 +239,15 @@ metric: {'Loss': 1.778, 'Top1-Acc':0.788, 'Top5-Acc':0.942} | |||
| #### Inference Performance | |||
| | Parameters | InceptionV3 | | |||
| | Parameters | Ascend | | |||
| | ------------------- | --------------------------- | | |||
| | Model Version | V1 | | |||
| | Resource | Ascend 910 | | |||
| | Uploaded Date | 08/22/2020 (month/day/year) | | |||
| | Model Version | InceptionV3 | | |||
| | Resource | Ascend 910, cpu:2.60GHz 56cores, memory:314G | | |||
| | Uploaded Date | 08/22/2020 | | |||
| | MindSpore Version | 0.6.0-beta | | |||
| | Dataset | 50k images | | |||
| | batch_size | 128 | | |||
| | outputs | probability | | |||
| | Batch_size | 128 | | |||
| | Outputs | probability | | |||
| | Accuracy | ACC1[78.8%] ACC5[94.2%] | | |||
| | Total time | 2mins | | |||
| | Model for inference | 92M (.onnx file) | | |||