learning_rate: 0.001
train_batch_size: 4
eval_batch_size: 8
seed: 42
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
num_epochs: 4
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
6.0192	0.2132	100	4.4580	0.9999
3.5904	0.4264	200	3.1478	1.0
2.5173	0.6397	300	0.3987	0.4625
0.2948	0.8529	400	0.2442	0.3075
0.2407	1.0661	500	0.2367	0.3170
0.2278	1.2793	600	0.2280	0.2914
0.2279	1.4925	700	0.2341	0.2963
0.2097	1.7058	800	0.2303	0.3138
0.2317	1.9190	900	0.2253	0.2889
0.1898	2.1322	1000	0.2187	0.2795
0.1925	2.3454	1100	0.2262	0.2951
0.211	2.5586	1200	0.2205	0.2909
0.1942	2.7719	1300	0.2192	0.2792
0.169	2.9851	1400	0.2213	0.2835
0.178	3.1983	1500	0.2148	0.2795
0.1862	3.4115	1600	0.2145	0.2803
0.1896	3.6247	1700	0.2154	0.2788
0.1813	3.8380	1800	0.2140	0.2772

MatricariaV/Yakut-ASR

Yakut-ASR