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eng-ind-tok_budget_weighted – AI Model by aroot | AlphaNeural AI
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eng-ind-tok_budget_weighted
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transformers
pytorch
tensorboard
mbart
text2text-generation
translation
generated_from_trainer
endpoints_compatible
us
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eng-ind-tok_budget_weighted
This model is a fine-tuned version of
facebook/mbart-large-50-many-to-many-mmt
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.8420
Bleu: 20.7842
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.26.1
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
