---
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
---