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ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-13k_onset-drums_fold_2

This model is a fine-tuned version of gary109/ai-light-dance_drums_ft_pretrain_wav2vec2-base-new-13k_onset-drums_fold_1 on the GARY109/AI_LIGHT_DANCE - ONSET-DRUMS_FOLD_2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4180
  • Wer: 0.1433

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • 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
0.3238 0.99 69 0.4581 0.2081
0.275 1.99 138 0.6494 0.3343
0.2965 2.99 207 0.6193 0.2275
0.3406 3.99 276 0.6934 0.2615
0.3906 4.99 345 0.6265 0.1835
0.4643 5.99 414 0.5879 0.1899
0.4652 6.99 483 0.4961 0.1604
0.4512 7.99 552 0.5712 0.2801
0.5321 8.99 621 0.6898 0.2936
0.64 9.99 690 0.5916 0.2648
0.2959 10.99 759 0.5574 0.1745
0.2053 11.99 828 0.5216 0.2009
0.2433 12.99 897 0.4738 0.1643
0.2036 13.99 966 0.5063 0.1651
0.2654 14.99 1035 0.4904 0.1511
0.3641 15.99 1104 0.4660 0.1669
0.373 16.99 1173 0.5133 0.2106
0.4715 17.99 1242 0.5313 0.1912
0.4893 18.99 1311 0.5152 0.1712
0.4875 19.99 1380 0.5482 0.1718
0.1971 20.99 1449 0.4566 0.1449
0.1286 21.99 1518 0.4515 0.1478
0.1472 22.99 1587 0.5059 0.1418
0.1917 23.99 1656 0.5583 0.1457
0.2874 24.99 1725 0.5195 0.1503
0.2252 25.99 1794 0.4409 0.1506
0.3142 26.99 1863 0.4180 0.1433
0.385 27.99 1932 0.4708 0.1367
0.4296 28.99 2001 0.4740 0.1506
0.4404 29.99 2070 0.4652 0.1646
0.2466 30.99 2139 0.5013 0.1528
0.1017 31.99 2208 0.4578 0.1552
0.1383 32.99 2277 0.5026 0.1419
0.1719 33.99 2346 0.4651 0.1442
0.1808 34.99 2415 0.4499 0.1412
0.2429 35.99 2484 0.4523 0.1472
0.2651 36.99 2553 0.4544 0.1397
0.2748 37.99 2622 0.4181 0.1386
0.4171 38.99 2691 0.4385 0.1334
0.4119 39.99 2760 0.4568 0.1504
0.1453 40.99 2829 0.4425 0.1431
0.105 41.99 2898 0.4367 0.1353
0.1205 42.99 2967 0.4418 0.1340
0.2039 43.99 3036 0.4586 0.1379
0.1773 44.99 3105 0.4686 0.1391
0.2186 45.99 3174 0.4975 0.1446
0.2358 46.99 3243 0.4886 0.1448
0.3525 47.99 3312 0.4706 0.1398
0.3713 48.99 3381 0.4713 0.1388
0.3543 49.99 3450 0.4720 0.1388

Framework versions

  • Transformers 4.24.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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