learning_rate: 1e-05
train_batch_size: 4
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 1000
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
2.2591	16.8889	50	nan
1.7534	33.4444	100	nan
1.446	50.0	150	nan
1.3861	66.8889	200	nan
1.2551	83.4444	250	nan
1.1811	100.0	300	nan
1.1416	116.8889	350	nan
1.0839	133.4444	400	nan
1.0502	150.0	450	nan
1.0335	166.8889	500	nan
1.0372	183.4444	550	nan
1.0037	200.0	600	nan
0.9739	216.8889	650	nan
1.027	233.4444	700	nan
0.9747	250.0	750	nan
0.9857	266.8889	800	nan
0.9798	283.4444	850	nan
0.9619	300.0	900	nan
0.9532	316.8889	950	nan
0.9474	333.4444	1000	nan

Birma/speecht5_finetuned_zarma

speecht5_finetuned_zarma