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mbart-neutralization – AI Model by jessgomesgomez | AlphaNeural AI
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mbart-neutralization
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transformers
tensorboard
safetensors
t5
text2text-generation
simplification
generated_from_trainer
facebook/mbart-large-50
finetune
mit
text-generation-inference
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: 0.0220
Bleu: 98.2132
Gen Len: 18.5417
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: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
Gen Len
No log
1.0
440
0.0490
96.2659
19.0104
0.2462
2.0
880
0.0220
98.2132
18.5417
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
