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ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
gary109/AI_Light_Dance
Generated from Trainer
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ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1
    results: []

ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1

This model is a fine-tuned version of gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5592
  • Wer: 0.2671

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: 8e-06
  • 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: 5000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4853 1.0 288 0.5760 0.3098
0.48 2.0 576 0.5787 0.3085
0.4625 3.0 864 0.5925 0.3112
0.4704 4.0 1152 0.6065 0.3108
0.4854 5.0 1440 0.6036 0.3112
0.4918 6.0 1728 0.6007 0.3148
0.4549 7.0 2016 0.6039 0.3073
0.4546 8.0 2304 0.6129 0.3073
0.4404 9.0 2592 0.6062 0.3054
0.4681 10.0 2880 0.6063 0.3075
0.469 11.0 3168 0.5881 0.3031
0.4903 12.0 3456 0.5913 0.3047
0.4677 13.0 3744 0.5921 0.3055
0.502 14.0 4032 0.5905 0.3042
0.5028 15.0 4320 0.5989 0.3088
0.4706 16.0 4608 0.5665 0.3066
0.4839 17.0 4896 0.6003 0.3111
0.4733 18.0 5184 0.5937 0.3039
0.4544 19.0 5472 0.5903 0.3025
0.4616 20.0 5760 0.6064 0.2968
0.475 21.0 6048 0.5883 0.2960
0.4707 22.0 6336 0.5900 0.2888
0.4562 23.0 6624 0.5642 0.2956
0.455 24.0 6912 0.5732 0.2893
0.5011 25.0 7200 0.5612 0.2876
0.4658 26.0 7488 0.5631 0.2915
0.4423 27.0 7776 0.5668 0.2853
0.4287 28.0 8064 0.5664 0.2847
0.4634 29.0 8352 0.5687 0.2875
0.4413 30.0 8640 0.5684 0.2954
0.4385 31.0 8928 0.5602 0.2801
0.4557 32.0 9216 0.5637 0.2747
0.4344 33.0 9504 0.5690 0.2853
0.4264 34.0 9792 0.5653 0.2866
0.4395 35.0 10080 0.5764 0.2808
0.4278 36.0 10368 0.5758 0.2761
0.44 37.0 10656 0.5816 0.2770
0.4356 38.0 10944 0.5814 0.2784
0.487 39.0 11232 0.5694 0.2834
0.44 40.0 11520 0.5637 0.2747
0.4151 41.0 11808 0.5683 0.2763
0.4208 42.0 12096 0.5720 0.2732
0.4354 43.0 12384 0.5657 0.2771
0.4304 44.0 12672 0.5735 0.2724
0.3991 45.0 12960 0.5638 0.2688
0.4348 46.0 13248 0.5639 0.2699
0.4291 47.0 13536 0.5577 0.2682
0.4252 48.0 13824 0.5611 0.2680
0.4253 49.0 14112 0.5621 0.2682
0.4298 50.0 14400 0.5592 0.2671

Framework versions

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