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dhasmana/Rajasthani-Magadhi-Chhattisgarhi-Bhojpuri-w2v-bert-2.0

sourceHugging Facemitupdated 7mo agoView on Hugging Face
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Rajasthani-Magadhi-Chhattisgarhi-Bhojpuri-w2v-bert-2.0

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.0989
  • —Cer: 0.1934

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
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 32
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossCer
5.59010.61863001.10500.2548
1.79431.23716000.99020.2170
1.47701.85579000.91390.2426
1.13312.474212000.89160.1998
0.93843.092815000.96590.2013
0.71793.711318000.96580.1939
0.53104.329921001.08820.1956
0.40044.948524001.11780.1984
0.25115.567027001.31120.1985
0.18496.185630001.39490.1990
0.11806.804133001.55430.1959
0.07727.422736001.67830.1980
0.05868.041239001.81470.1977
0.03308.659842001.99580.1934
0.02139.278445002.05100.1942
0.01379.896948002.09890.1934

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.9.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2