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callmesan/indic-bert-roman-urdu-fine-grained

sourceHugging Facemitupdated 2y agoView on Hugging Face
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indic-bert-roman-urdu-fine-grained

This model is a fine-tuned version of ai4bharat/indic-bert on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8501
  • Accuracy: 0.7678
  • Precision: 0.6945
  • Recall: 0.6537
  • F1: 0.6720

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: 32
  • evalbatchsize: 128
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
1.12371.01131.09470.53420.10680.20.1393
0.96062.02260.87760.66890.44560.31880.2779
0.77843.03390.64430.78960.70170.68300.6899
0.56264.04520.51670.83020.75610.73710.7422
0.56135.05650.42850.86340.79310.78490.7850
0.42326.06780.35430.88670.82950.80720.8155
0.33767.07910.25460.92930.88500.87570.8802
0.27598.09040.20790.94690.90850.91320.9103
0.20299.010170.15640.96060.93700.92760.9322
0.13710.011300.13640.96850.95580.93990.9477

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0