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mbart-neutralization – AI Model by marinatamayo | AlphaNeural AI
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mbart-neutralization
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transformers
safetensors
mbart
text2text-generation
simplification
generated_from_trainer
facebook/mbart-large-50
finetune
mit
endpoints_compatible
us
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mbart-neutralization
This model is a fine-tuned version of
facebook/mbart-large-50
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0426
Bleu: 95.7463
Gen Len: 18.4479
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: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAFACTOR and the args are: 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
Gen Len
No log
1.0
88
0.0810
95.2839
18.3646
No log
2.0
176
0.0426
95.7463
18.4479
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.8.2
Tokenizers 0.22.2
