learning_rate: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
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_ratio: 0.1
num_epochs: 15

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Sensitivity
No log	0.8571	3	1.1235	0.2647	0.1108	0.0701	0.2647	0.2647
No log	2.0	7	1.1253	0.2647	0.1108	0.0701	0.2647	0.2647
1.0608	2.8571	10	1.1178	0.2647	0.1162	0.0744	0.2647	0.2647
1.0608	4.0	14	1.1206	0.2941	0.1740	0.4886	0.2941	0.2941
1.0608	4.8571	17	1.1225	0.2941	0.2083	0.3475	0.2941	0.2941
0.9214	6.0	21	1.1167	0.4412	0.4108	0.5259	0.4412	0.4412
0.9214	6.8571	24	1.0754	0.5	0.4625	0.4954	0.5	0.5
0.9214	8.0	28	1.1578	0.4118	0.3959	0.4304	0.4118	0.4118
0.6179	8.8571	31	1.2143	0.3824	0.3663	0.4120	0.3824	0.3824
0.6179	10.0	35	1.3170	0.4118	0.4169	0.5174	0.4118	0.4118
0.6179	10.8571	38	1.3484	0.3529	0.3484	0.4777	0.3529	0.3529
0.3513	12.0	42	1.3904	0.3235	0.3095	0.4512	0.3235	0.3235
0.3513	12.8571	45	1.3900	0.3235	0.3095	0.4512	0.3235	0.3235

sarasarasara/whisper-base-finetuned-bmd

whisper-base-finetuned-bmd