opus-mt-neutralization

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

• Loss: 0.2754
• Bleu: 90.7445
• Gen Len: 15.6562

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: 0.0005
• train_batch_size: 16
• eval_batch_size: 16
• 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
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	220	0.5899	82.714	15.7188
No log	2.0	440	0.3990	87.6984	15.5
0.2663	3.0	660	0.2754	90.7445	15.6562

Framework versions

• Transformers 4.51.2
• Pytorch 2.10.0+cu128
• Datasets 4.8.2
• Tokenizers 0.21.4