audioclass-alpha

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0963
• Accuracy: 0.9819

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: 3e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.3678	1.0	62	3.3612	0.0408
3.349	2.0	124	3.3402	0.0385
3.2935	3.0	186	3.2047	0.2494
2.9643	4.0	248	2.7250	0.5102
2.4158	5.0	310	2.1914	0.6621
1.9634	6.0	372	1.7440	0.7800
1.6144	7.0	434	1.3680	0.8503
1.2939	8.0	496	1.0948	0.8390
1.0933	9.0	558	0.8783	0.8776
0.8596	10.0	620	0.7053	0.9048
0.6664	11.0	682	0.6020	0.9184
0.5843	12.0	744	0.5392	0.9048
0.5714	13.0	806	0.4380	0.9297
0.4395	14.0	868	0.4434	0.9252
0.323	15.0	930	0.3000	0.9524
0.3218	16.0	992	0.2418	0.9546
0.3026	17.0	1054	0.2462	0.9524
0.2531	18.0	1116	0.2003	0.9660
0.2702	19.0	1178	0.1883	0.9637
0.2368	20.0	1240	0.1612	0.9728
0.2121	21.0	1302	0.1981	0.9637
0.2011	22.0	1364	0.1635	0.9683
0.1875	23.0	1426	0.1454	0.9728
0.1415	24.0	1488	0.1433	0.9683
0.1162	25.0	1550	0.1504	0.9660
0.0946	26.0	1612	0.1759	0.9615
0.1032	27.0	1674	0.1206	0.9751
0.095	28.0	1736	0.1123	0.9773
0.1526	29.0	1798	0.1267	0.9728
0.1003	30.0	1860	0.0953	0.9796
0.1371	31.0	1922	0.1158	0.9751
0.0765	32.0	1984	0.0963	0.9819
0.1152	33.0	2046	0.0929	0.9819
0.1344	34.0	2108	0.1103	0.9796
0.1067	35.0	2170	0.1065	0.9773
0.0847	36.0	2232	0.0898	0.9819
0.0835	37.0	2294	0.0934	0.9819
0.1009	38.0	2356	0.1136	0.9796
0.1272	39.0	2418	0.1315	0.9751
0.0463	40.0	2480	0.1127	0.9796
0.085	41.0	2542	0.0985	0.9796
0.0431	42.0	2604	0.0964	0.9773
0.0698	43.0	2666	0.1128	0.9773
0.0493	44.0	2728	0.0934	0.9796
0.1208	45.0	2790	0.0882	0.9819
0.0536	46.0	2852	0.0932	0.9796
0.064	47.0	2914	0.1008	0.9796
0.0538	48.0	2976	0.1094	0.9796
0.0774	49.0	3038	0.1081	0.9796
0.0379	50.0	3100	0.1085	0.9796

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1