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Finetuned-hindi-to-english-V5

This model is a fine-tuned version of Helsinki-NLP/opus-mt-hi-en on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.3700
  • Rouge1: 46.8571
  • Rouge2: 20.4177
  • Rougel: 41.8681
  • Rougelsum: 41.979
  • Gen Len: 25.9805

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.9003 1.0 500 3.5309 44.7687 19.3162 39.7482 39.8743 47.273
3.3953 2.0 1000 3.4295 45.583 19.7519 40.5147 40.6327 31.2255
3.1149 3.0 1500 3.3829 45.9163 19.8789 41.0229 41.1501 34.532
2.9111 4.0 2000 3.3663 45.9453 19.9925 41.0019 41.1038 32.6625
2.7429 5.0 2500 3.3609 46.2821 20.1008 41.2762 41.389 29.1325
2.6212 6.0 3000 3.3592 46.3719 20.2255 41.2826 41.4093 28.0275
2.5156 7.0 3500 3.3632 46.5546 20.3336 41.5246 41.627 25.3715
2.4429 8.0 4000 3.3646 46.5347 20.2066 41.5536 41.6628 27.2935
2.3909 9.0 4500 3.3689 46.9327 20.3823 41.8767 41.9965 25.751
2.358 10.0 5000 3.3700 46.8571 20.4177 41.8681 41.979 25.9805

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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