tensorflow / tensorflow/models
incremental training with output model
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@pkulzc is already working on this.
Since Jun 19, 2020.
models:research:odapi
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Description
I have trained my dataset on ssd_mobilenet_v1_coco model. I'm getting continuous incremental data. Right now my dataset is very limited
What I want to achieve is. Incremental training. So as soon as I get new data I can further train my already trained model & don't have redo train everything
{ Save Trained Model -> New Data -> Train on Old model } Loop
between it's transfer learning essentially. Correct me if wrong. But how do I do it on my own saved model
System information
- What is the top-level directory of the model you are using:
- Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
- TensorFlow installed from (source or binary): TensorFlow installed with pip
- TensorFlow version (use command below): 1.13.1
- Bazel version (if compiling from source):
- CUDA/cuDNN version: V10.1.168/7.*
- GPU model and memory: 2080Ti 11Gb
- Exact command to reproduce:
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