Different training result when project upgraded to new ML-Agents version

I have used ML-Agents v0.6 for quite some time for my research. Recently, I want to use some functionalities of the newer version so I have tried v0.10 for the old project. The problem is, after adjusting various parameters in the configuration file as in https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Migrating.md, the result is, well, just slightly different. Imagine that with the 0.6 version, the output of a Vector Action element ranges from 0.04 to 0.06, for example; the output of that using the 0.10 version is 0.02 to 0.08.

Below is my config.yaml files
version 0.6

default:

    trainer: ppo

    batch_size: 20480

    beta: 5.0e-3

    buffer_size: 204800

    epsilon: 0.1

    gamma: 0.6

    hidden_units: 512

    lambd: 0.9

    learning_rate: 1.5e-3

    max_steps: 3e6

    memory_size: 256

    normalize: false

    num_epoch: 3

    num_layers: 3

    time_horizon: 3000

    sequence_length: 64

    summary_freq: 1000

    use_recurrent: false   

    use_curiosity: false

    curiosity_strength: 0.01

    curiosity_enc_size: 128

version 0.10

default:

    trainer: ppo

    batch_size: 20480

    beta: 5.0e-3

    buffer_size: 204800

    epsilon: 0.1

    hidden_units: 512

    lambd: 0.9

    learning_rate: 1.5e-3

    learning_rate_schedule: linear

    max_steps: 3e6

    memory_size: 256

    normalize: false

    num_epoch: 3

    num_layers: 3

    time_horizon: 3000

    sequence_length: 64

    summary_freq: 1000

    use_recurrent: false

    vis_encode_type: simple

    reward_signals:

        extrinsic:

            strength: 1.0

            gamma: 0.6

I am not sure what I'm doing wrong. Below is the TensorBoard for my two training, which looks really similar to me. The orange one is v0.6 and the blue one is v0.10



Thank you in advance!

 

I don't know where to find the console logs. As for Python and C#, my Python version is Python 3.6.9 (Anaconda) and .NET version is 4.8.