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SIR51/banglabert-movie-sentiment

sourceHugging Faceupdated 8d agoView on Hugging Face
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banglabert-movie-sentiment

This model is a fine-tuned version of csebuetnlp/banglabert on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0953
  • —Accuracy: 0.8338
  • —F1 Macro: 0.6659
  • —F1 Weighted: 0.8257
  • —Precision: 0.6836
  • —Recall: 0.6546

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: 64
  • —seed: 42
  • —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: 0.1
  • —num_epochs: 5
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1 MacroF1 WeightedPrecisionRecall
1.20311.01781.14950.79440.52050.75180.51900.5300
0.87742.03560.91510.83520.57420.80230.59320.6002
0.68583.05341.00840.82390.58600.80230.58660.6087
0.49394.07121.07640.82390.62950.81520.63560.6283
0.46195.08901.12340.82820.63660.81960.64570.6313

Framework versions

  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 5.0.0
  • —Tokenizers 0.22.2