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ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
gary109/AI_Light_Dance
Generated from Trainer
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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-v1-5gram
    results: []

ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram

This model is a fine-tuned version of gary109/ai-light-dance_singing3_ft_wav2vec2-large-xlsr-53-v1-5gram on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4904
  • Wer: 0.2087

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.504 1.0 72 0.4810 0.2313
0.5274 2.0 144 0.4828 0.2388
0.5021 3.0 216 0.5008 0.2409
0.4956 4.0 288 0.4897 0.2401
0.543 5.0 360 0.5795 0.2473
0.5239 6.0 432 0.5019 0.2490
0.4928 7.0 504 0.4563 0.2312
0.5236 8.0 576 0.5311 0.2648
0.5059 9.0 648 0.4729 0.2294
0.5064 10.0 720 0.5001 0.2464
0.5032 11.0 792 0.4968 0.2335
0.5064 12.0 864 0.5238 0.2365
0.5001 13.0 936 0.4774 0.2325
0.5003 14.0 1008 0.4961 0.2339
0.5085 15.0 1080 0.4646 0.2271
0.4931 16.0 1152 0.5007 0.2320
0.4807 17.0 1224 0.4818 0.2258
0.4894 18.0 1296 0.4954 0.2311
0.4746 19.0 1368 0.4951 0.2293
0.4795 20.0 1440 0.4873 0.2304
0.4964 21.0 1512 0.4998 0.2431
0.4947 22.0 1584 0.4986 0.2324
0.4789 23.0 1656 0.5380 0.2381
0.4603 24.0 1728 0.4819 0.2339
0.4591 25.0 1800 0.4869 0.2202
0.4675 26.0 1872 0.4873 0.2214
0.4777 27.0 1944 0.4872 0.2291
0.475 28.0 2016 0.4920 0.2285
0.4921 29.0 2088 0.4855 0.2223
0.4875 30.0 2160 0.4978 0.2211
0.4699 31.0 2232 0.4962 0.2336
0.4787 32.0 2304 0.5130 0.2276
0.4631 33.0 2376 0.5091 0.2258
0.4697 34.0 2448 0.5217 0.2480
0.4677 35.0 2520 0.4852 0.2254
0.4644 36.0 2592 0.5171 0.2333
0.476 37.0 2664 0.4745 0.2209
0.4491 38.0 2736 0.4898 0.2282
0.4432 39.0 2808 0.4738 0.2237
0.4804 40.0 2880 0.4744 0.2245
0.4479 41.0 2952 0.5006 0.2202
0.4379 42.0 3024 0.4752 0.2214
0.4412 43.0 3096 0.4722 0.2211
0.4459 44.0 3168 0.4859 0.2203
0.4541 45.0 3240 0.4850 0.2189
0.4509 46.0 3312 0.4838 0.2162
0.4472 47.0 3384 0.4893 0.2311
0.4341 48.0 3456 0.4900 0.2198
0.4306 49.0 3528 0.5052 0.2166
0.44 50.0 3600 0.5087 0.2230
0.4425 51.0 3672 0.4850 0.2200
0.4329 52.0 3744 0.4713 0.2189
0.4335 53.0 3816 0.4829 0.2138
0.4184 54.0 3888 0.5034 0.2128
0.4303 55.0 3960 0.4945 0.2166
0.4519 56.0 4032 0.5089 0.2106
0.4336 57.0 4104 0.5325 0.2146
0.4274 58.0 4176 0.5189 0.2220
0.4217 59.0 4248 0.5071 0.2119
0.4173 60.0 4320 0.5163 0.2185
0.4221 61.0 4392 0.4850 0.2189
0.4244 62.0 4464 0.4900 0.2153
0.4147 63.0 4536 0.4966 0.2078
0.4135 64.0 4608 0.5243 0.2166
0.4127 65.0 4680 0.4889 0.2164
0.3979 66.0 4752 0.4928 0.2173
0.4151 67.0 4824 0.4978 0.2132
0.4157 68.0 4896 0.5227 0.2169
0.4135 69.0 4968 0.4866 0.2130
0.4109 70.0 5040 0.4848 0.2094
0.4084 71.0 5112 0.5012 0.2168
0.4078 72.0 5184 0.4836 0.2186
0.4106 73.0 5256 0.4835 0.2132
0.3977 74.0 5328 0.5025 0.2151
0.4056 75.0 5400 0.4893 0.2191
0.4019 76.0 5472 0.4853 0.2108
0.4147 77.0 5544 0.4849 0.2131
0.4075 78.0 5616 0.5036 0.2117
0.4064 79.0 5688 0.4793 0.2133
0.4035 80.0 5760 0.4917 0.2083
0.4083 81.0 5832 0.4725 0.2116
0.3954 82.0 5904 0.4958 0.2119
0.395 83.0 5976 0.4898 0.2135
0.391 84.0 6048 0.4822 0.2151
0.3983 85.0 6120 0.4809 0.2110
0.3883 86.0 6192 0.4981 0.2108
0.3955 87.0 6264 0.4877 0.2111
0.3983 88.0 6336 0.4879 0.2135
0.3877 89.0 6408 0.5022 0.2150
0.3992 90.0 6480 0.5071 0.2117
0.393 91.0 6552 0.4834 0.2108
0.3941 92.0 6624 0.4962 0.2119
0.3877 93.0 6696 0.4879 0.2076
0.3709 94.0 6768 0.4877 0.2090
0.3905 95.0 6840 0.4970 0.2130
0.3918 96.0 6912 0.4895 0.2106
0.3954 97.0 6984 0.4884 0.2079
0.3979 98.0 7056 0.4895 0.2097
0.373 99.0 7128 0.4875 0.2076
0.3769 100.0 7200 0.4904 0.2087

Framework versions

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