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Naren-Kandasamy/indicbert_tmp

sourceHugging Facemitupdated 8mo agoView on Hugging Face
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Model Card

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indicbert_tmp

This model is a fine-tuned version of ai4bharat/IndicBERTv2-MLM-only on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.9940
  • —Accuracy: 0.3435
  • —F1: 0.3684

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: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 0.1
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1
No log1.04351.74490.25460.2496
1.73852.08701.66500.34840.3423
1.31333.013051.83280.34230.3699
0.89074.017402.09180.32890.3622
0.53375.021752.25730.33010.3606
0.33056.026102.57530.33620.3612
0.20917.030452.73160.34470.3660
0.20918.034802.87910.34470.3550
0.14799.039152.98680.33980.3679
0.111410.043502.99400.34350.3684

Framework versions

  • —Transformers 5.1.0
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2