learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
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_ratio: 0.1
num_epochs: 70
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.8755	1.0	7125	0.3901	0.4546	0.0912
0.1904	2.0	14250	0.3507	0.4646	0.0896
0.1641	3.0	21375	0.3312	0.4389	0.0854
0.1511	4.0	28500	0.3229	0.4311	0.0802
0.145	5.0	35625	0.3518	0.4273	0.0820
0.1406	6.0	42750	0.3275	0.4302	0.0812
0.1379	7.0	49875	0.3627	0.5317	0.0944
0.1316	8.0	57000	0.3234	0.4175	0.0817
0.1182	9.0	64125	0.3534	0.4317	0.0819
0.1082	10.0	71250	0.3230	0.4053	0.0777
0.0976	11.0	78375	0.3261	0.4194	0.0791
0.0884	12.0	85500	0.3183	0.4119	0.0798
0.0803	13.0	92625	0.3695	0.4170	0.0791
0.072	14.0	99750	0.3596	0.4102	0.0799
0.0637	15.0	106875	0.3625	0.4137	0.0803
0.0554	16.0	114000	0.3958	0.4336	0.0822
0.0481	17.0	121125	0.3820	0.4128	0.0796
0.0422	18.0	128250	0.4239	0.4134	0.0807
0.0357	19.0	135375	0.3978	0.4436	0.0839
0.031	20.0	142500	0.4163	0.4201	0.0816

asr-africa/w2v-bert-2.0-lg-CV-Fleurs-filtered-100hrs-v11

w2v-bert-2.0-lg-CV-Fleurs-filtered-100hrs-v11