ai-light-dance_chord_ft_wav2vec2-large-xlsr-53

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the GARY109/AI_LIGHT_DANCE - ONSET-CHORD2 dataset. It achieves the following results on the evaluation set:

• Loss: 1.8722
• Wer: 0.9590

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: 10
• eval_batch_size: 10
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 160
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 50.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.1857	1.0	126	4.5913	1.0
3.0939	2.0	252	3.0160	1.0
2.8403	3.0	378	2.7337	1.0
2.2525	4.0	504	2.5588	0.9825
2.0291	5.0	630	2.5216	0.9701
1.9083	6.0	756	2.3990	0.9514
1.8745	7.0	882	2.2781	0.9474
1.8222	8.0	1008	2.2360	0.9471
1.7871	9.0	1134	2.1960	0.9463
1.7225	10.0	1260	2.0775	0.9464
1.6856	11.0	1386	2.0817	0.9518
1.6903	12.0	1512	2.0607	0.9534
1.6034	13.0	1638	1.9956	0.9504
1.6171	14.0	1764	2.0099	0.9490
1.5508	15.0	1890	2.0424	0.9591
1.539	16.0	2016	1.9728	0.9600
1.5176	17.0	2142	2.0421	0.9628
1.5088	18.0	2268	1.9428	0.9598
1.4739	19.0	2394	1.9886	0.9591
1.4228	20.0	2520	2.0164	0.9670
1.4277	21.0	2646	1.9968	0.9704
1.3834	22.0	2772	1.9882	0.9669
1.3768	23.0	2898	1.9519	0.9606
1.3747	24.0	3024	1.8923	0.9580
1.3533	25.0	3150	1.9767	0.9707
1.3312	26.0	3276	1.8993	0.9609
1.2743	27.0	3402	1.9494	0.9705
1.2924	28.0	3528	1.9019	0.9631
1.2621	29.0	3654	1.9110	0.9596
1.2387	30.0	3780	1.9118	0.9627
1.228	31.0	3906	1.8722	0.9590
1.1938	32.0	4032	1.8890	0.9599
1.1887	33.0	4158	1.9175	0.9653
1.1807	34.0	4284	1.8983	0.9649
1.1553	35.0	4410	1.9246	0.9703
1.1448	36.0	4536	1.9248	0.9705
1.1146	37.0	4662	1.9747	0.9804
1.1394	38.0	4788	1.9119	0.9723
1.1206	39.0	4914	1.8931	0.9630
1.0892	40.0	5040	1.9243	0.9668
1.104	41.0	5166	1.8965	0.9671
1.054	42.0	5292	1.9477	0.9755
1.0922	43.0	5418	1.8969	0.9699
1.0484	44.0	5544	1.9423	0.9733
1.0567	45.0	5670	1.9412	0.9745
1.0615	46.0	5796	1.9076	0.9674
1.0201	47.0	5922	1.9384	0.9743
1.0664	48.0	6048	1.9509	0.9816
1.0498	49.0	6174	1.9426	0.9757
1.0303	50.0	6300	1.9477	0.9781

Framework versions

• Transformers 4.21.0.dev0
• Pytorch 1.9.1+cu102
• Datasets 2.3.3.dev0
• Tokenizers 0.12.1