To elaborate more. During the training phase I get these outputs and respective targets for this regression problem:
tensor([-14.5732574463, -14.5583467484, -14.5344114304, -14.5010814667,
        -14.4517145157, -14.4076881409, -14.3827638626, -14.3705654144,
        -14.3653717041, -14.3649988174], grad_fn=<StackBackward>)
targets
tensor([-14.5868730545, -14.5640010834, -14.5292606354, -14.4874134064,
        -14.4443883896, -14.4063940048, -14.3788156509, -14.3651800156,
        -14.3665180206, -14.3813629150])

After loading the model from the state_dict this is what I get:
mlchem predicted energy = -14.418486595153809
mlchem predicted energy = -14.418549537658691
mlchem predicted energy = -14.418668746948242
mlchem predicted energy = -14.418920516967773
mlchem predicted energy = -14.419416427612305
mlchem predicted energy = -14.419506072998047
mlchem predicted energy = -14.419241905212402
mlchem predicted energy = -14.418638229370117
mlchem predicted energy = -14.41697883605957
mlchem predicted energy = -14.413832664489746