license: mit
- Model is directly from pytorch. Refer to the python file. To reuse, use .load_state_dict() from the .pth file. Good luck.
Training steps:
step 0: train loss 4.2221, val loss 4.2306
step 500: train loss 1.7526, val loss 1.9053
step 1000: train loss 1.3949, val loss 1.6050
step 1500: train loss 1.2625, val loss 1.5219
step 2000: train loss 1.1860, val loss 1.5046
step 2500: train loss 1.1254, val loss 1.4972
step 3000: train loss 1.0694, val loss 1.4849
step 3500: train loss 1.0211, val loss 1.5048
step 4000: train loss 0.9643, val loss 1.5160
step 4500: train loss 0.9121, val loss 1.5396
step 5000: train loss 0.8673, val loss 1.5552
step 5500: train loss 0.8052, val loss 1.5988
step 6000: train loss 0.7611, val loss 1.6231
step 6500: train loss 0.7087, val loss 1.6706
step 7000: train loss 0.6644, val loss 1.7000
step 7500: train loss 0.6187, val loss 1.7484
step 8000: train loss 0.5818, val loss 1.7882
step 8500: train loss 0.5350, val loss 1.8304
step 9000: train loss 0.4973, val loss 1.8688
step 9500: train loss 0.4638, val loss 1.9050
step 9999: train loss 0.4333, val loss 1.9475