wav2vec2-base-mn-pretrain-42h-mn-silence-speech-commands

This model is a fine-tuned version of bayartsogt/wav2vec2-base-mn-pretrain-42h on the Mongolian Speech Commands dataset. It achieves the following results on the evaluation set:

• Loss: 0.0562
• Mn Acc: 0.9830
• Mn F1: 0.9832
• Silence Acc: 1.0
• Silence F1: 1.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Mn Acc	Mn F1	Silence Acc	Silence F1
No log	0.4	8	2.0276	0.0455	0.0239	1.0	1.0
2.3615	0.8	16	1.1112	0.0057	0.0108	1.0	1.0
2.0154	1.2	24	0.6836	0.6307	0.5627	0.9975	0.9988
1.5733	1.6	32	0.4493	0.7898	0.7652	0.9975	0.9988
1.1148	2.0	40	0.3264	0.8409	0.8202	1.0	1.0
1.1148	2.4	48	0.2490	0.8864	0.8768	1.0	1.0
0.7937	2.8	56	0.1739	0.9545	0.9540	1.0	1.0
0.586	3.2	64	0.1425	0.9659	0.9664	1.0	1.0
0.4445	3.6	72	0.1137	0.9659	0.9659	1.0	1.0
0.3892	4.0	80	0.0942	0.9773	0.9772	1.0	1.0
0.3892	4.4	88	0.0914	0.9716	0.9717	1.0	1.0
0.3341	4.8	96	0.0748	0.9773	0.9775	1.0	1.0
0.2863	5.2	104	0.0670	0.9886	0.9886	1.0	1.0
0.2622	5.6	112	0.0697	0.9830	0.9832	1.0	1.0
0.2222	6.0	120	0.0638	0.9830	0.9832	1.0	1.0
0.2222	6.4	128	0.0580	0.9886	0.9886	1.0	1.0
0.213	6.8	136	0.0575	0.9830	0.9832	1.0	1.0
0.2082	7.2	144	0.0587	0.9830	0.9832	1.0	1.0
0.202	7.6	152	0.0582	0.9830	0.9832	1.0	1.0
0.1936	8.0	160	0.0562	0.9830	0.9832	1.0	1.0

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.0
• Datasets 2.14.4
• Tokenizers 0.13.3