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mbart-neutralization – AI Model by jonruida | AlphaNeural AI
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jonruida
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mbart-neutralization
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transformers
tensorboard
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 the None dataset. It achieves the following results on the evaluation set:
Loss: 0.8104
Bleu: 55.4468
Gen Len: 128.309
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
1.2231
1.0
1054
0.8900
52.4669
126.9307
0.6727
2.0
2108
0.8104
55.4468
128.309
Framework versions
Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1
