learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: cosine
lr_scheduler_warmup_steps: 0.1
training_steps: 15000

Training Loss	Epoch	Step	Cer	Validation Loss	Wer
5.9489	0.2076	1500	1.0	3.0230	1.0
1.5319	0.4152	3000	0.5960	0.5589	0.1293
1.1602	0.6228	4500	0.4309	0.4809	0.1054
1.0148	0.8304	6000	0.3715	0.4499	0.0974
0.9507	1.0381	7500	0.3443	0.4274	0.0927
0.9469	1.2457	9000	0.3220	0.4031	0.0876
0.8564	1.4533	10500	0.3134	0.3995	0.0864
0.8318	1.6609	12000	0.3061	0.3951	0.0848
0.8707	1.8685	13500	0.3033	0.3904	0.0841
0.9274	2.0761	15000	0.3020	0.3905	0.0840

akera/w2vbert-ctc-salt

w2vbert-ctc-salt