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Chenchuhui/Icelandic-finetuned-data-augmentation

sourceHugging Facecc-by-4.0updated 3y agoView on Hugging Face
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Icelandicmodelaug_checkpoints

This model is a fine-tuned version of carlosdanielhernandezmena/wav2vec2-large-xlsr-53-icelandic-ep10-1000h on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2766
  • —Wer: 0.2136

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 16
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossWer
No log0.2100.68180.3244
No log0.4200.45700.2841
No log0.6300.42810.2562
No log0.8400.42840.2282
0.80091.0500.43350.2260
0.80091.2600.43020.2159
0.80091.4700.41130.2114
0.80091.6800.38470.2159
0.80091.8900.37950.2148
0.45672.01000.37160.2058
0.45672.21100.38480.2081
0.45672.41200.37970.2036
0.45672.61300.36950.2036
0.45672.81400.35450.1969
0.37233.01500.34330.1957
0.37233.21600.32130.1957
0.37233.41700.30680.1913
0.37233.61800.30490.1902
0.37233.81900.30390.1991
0.32594.02000.29860.1913
0.32594.22100.31810.1969
0.32594.42200.32160.1857
0.32594.62300.33360.1913
0.32594.82400.33170.1980
0.28095.02500.29480.2025
0.28095.22600.31650.1879
0.28095.42700.32890.2081
0.28095.62800.30710.1913
0.28095.82900.31160.1957
0.27116.03000.24410.2136
0.27116.23100.29610.2013
0.27116.43200.34730.2069
0.27116.63300.22010.2058
0.27116.83400.20040.1991
0.25787.03500.22130.2081
0.25787.23600.36980.2081
0.25787.43700.39210.2114
0.25787.63800.38610.2204
0.25787.83900.37920.2271
0.25038.04000.30840.2092
0.25038.24100.32730.2058
0.25038.44200.39650.2069
0.25038.64300.28380.2036
0.25038.84400.32430.2148
0.24859.04500.31390.2136
0.24859.24600.31550.2036
0.24859.44700.31400.2103
0.24859.64800.29020.2349
0.24859.84900.23890.2047
0.256710.05000.27660.2136

Framework versions

  • —Transformers 4.35.2
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.15.0
  • —Tokenizers 0.15.0