CoolFace
Modelpublic

rohitp1/libri-alpha-1-Temp-1-attention-4

sourceHugging Faceupdated 4y agoView on Hugging Face
0likes7downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

libri-alpha-1-Temp-1-attention-4

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 254.9241
  • Wer: 0.2989

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: 2e-05
  • trainbatchsize: 32
  • evalbatchsize: 32
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 30
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
1911.36860.75100495.11920.5273
1556.77641.49200406.38320.4759
1347.04472.24300371.96650.4413
1303.72592.99400350.53830.4145
1200.06943.73500336.20060.3933
1177.66884.48600325.61010.3803
1174.2245.22700318.79970.3697
1037.01715.97800310.22110.3616
1012.84026.72900301.00190.3544
1012.07727.461000295.52390.3495
956.34458.211100290.57950.3450
935.57938.961200286.10220.3408
955.96589.71300281.60910.3377
936.721210.451400278.77190.3349
863.061111.191500275.76890.3268
871.68611.941600274.43540.3296
891.186212.691700271.17850.3226
905.869213.431800269.13270.3209
840.966714.181900268.06690.3160
856.37414.932000266.19270.3174
853.352715.672100265.25820.3138
845.168616.422200265.04040.3135
863.862717.162300264.01610.3127
812.896217.912400262.05900.3104
791.297318.662500260.72500.3081
823.04719.42600260.49280.3057
808.342720.152700260.01930.3066
787.363820.92800258.63020.3057
788.961621.642900258.63510.3041
794.210222.393000258.33930.3027
805.296923.133100257.57510.3031
799.989123.883200257.00370.3034
784.621324.633300256.69110.3024
809.311625.373400255.79360.3005
790.449826.123500255.71680.3001
778.962726.873600255.72480.2995
754.241227.613700255.33480.3000
778.78528.363800254.88430.2991
754.362329.13900255.06640.2991
803.026629.854000254.92410.2989

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1
  • Datasets 2.7.0
  • Tokenizers 0.11.0