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dpraitality/experts_3split_wav2vec2-large-xls-r-300m-dm32

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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experts3splitwav2vec2-large-xls-r-300m-dm32

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.6181
  • —Accuracy: 0.4149
  • —Acc Dem 0: 0.0
  • —Acc Dem 10: 0.0
  • —Acc Dem 15: 0.0
  • —Acc Dem 5: 0.0833
  • —Acc No 1: 0.6190
  • —Acc No 2: 0.3158
  • —Acc No 3: 0.7308
  • —Binary Dem Accuracy: 1.0
  • —Binary Dem F1: 1.0

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: 0.0001
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 22
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyAcc Dem 0Acc Dem 10Acc Dem 15Acc Dem 5Acc No 1Acc No 2Acc No 3Binary Dem AccuracyBinary Dem F1
No log2.0341.79140.26600.00.00.00.00.00.00.96151.01.0
No log4.0681.76990.25530.00.00.00.00.00.10530.84621.01.0
No log6.01021.78390.26600.00.00.00.00.00.10530.88461.01.0
1.77868.01361.79590.20210.00.00.00.00.01.00.01.01.0
1.778610.01701.76810.22340.00.00.00.00.33330.73680.01.01.0
1.778612.02041.71080.34040.00.00.00.00.33330.10530.88461.01.0
1.737614.02381.70890.38300.00.00.00.00.38100.15790.96151.01.0
1.737616.02721.63530.43620.00.00.00.00.61900.21050.92311.01.0
1.737618.03061.61610.43620.00.00.00.08330.57140.21050.92311.01.0
1.532320.03401.61720.39360.00.00.00.00.61900.26320.73081.01.0
1.532322.03741.61810.41490.00.00.00.08330.61900.31580.73081.01.0

Framework versions

  • —Transformers 4.57.2
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1