learning_rate: 0.0001
train_batch_size: 4
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use adamw_torch 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: 100
training_steps: 1500
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
0.648	7.9901	100	0.5922
0.5721	15.9901	200	0.5445
0.5337	23.9901	300	0.5103
0.5057	31.9901	400	0.5052
0.4894	39.9901	500	0.4869
0.4765	47.9901	600	0.4804
0.4577	55.9901	700	0.4770
0.4462	63.9901	800	0.4561
0.4275	71.9901	900	0.4445
0.4143	79.9901	1000	0.4388
0.4044	87.9901	1100	0.4363
0.3929	95.9901	1200	0.4299
0.3922	103.9901	1300	0.4276
0.3915	111.9901	1400	0.4262
0.3877	119.9901	1500	0.4253

binisha/speecht5_finetuned_binisha

speecht5_finetuned_binisha