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hai2131/
mt-en-vi

Name: mt-en-vi
Availability: InStock

generated_from_trainer

thainq107/iwslt2015-en-vi

facebook/mbart-large-50-many-to-many-mmt

finetune

endpoints_compatible

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mt-en-vi

This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on a dataset from iwslt2015. It achieves the following results on the evaluation set:

Loss: 1.2564
Bleu: 34.9585

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: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu
1.1887	0.2399	500	1.2961	34.2118
1.1422	0.4798	1000	1.2807	34.6929
1.127	0.7198	1500	1.2689	34.7625
1.1215	0.9597	2000	1.2577	34.5726
1.031	1.1996	2500	1.2728	35.0683
1.0128	1.4395	3000	1.2632	34.8100
1.0184	1.6795	3500	1.2565	34.7721
1.0131	1.9194	4000	1.2564	34.9585

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 2.20.0
Tokenizers 0.21.1

hai2131/mt-en-vi

mt-en-vi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hai2131/
mt-en-vi