Reduce total training iterations to 800k

Signed-off-by: begeekmyfriend <[email protected]>

hparams.py

@@ -50,7 +50,7 @@
 voc_final_lr = 1e-5
 voc_checkpoint_every = 50_000
 voc_gen_at_checkpoint = 5           # number of samples to generate at each checkpoint
-voc_total_steps = 1_000_000         # Total number of training steps
+voc_total_steps = 800_000           # Total number of training steps
 voc_test_samples = 50               # How many unseen samples to put aside for testing
 voc_pad = 2                         # this will pad the input so that the resnet can 'see' wider than input length
 voc_pad_val = -10                   # this is the minimum of mel features