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bart-large-samsum – AI Model by roiyeho | AlphaNeural AI
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bart-large-samsum
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transformers
tensorboard
safetensors
bart
text2text-generation
summarization
generated_from_trainer
facebook/bart-large-cnn
finetune
mit
endpoints_compatible
us
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bart-large-samsum
This model is a fine-tuned version of
facebook/bart-large-cnn
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3635
Rouge1: 0.3962
Rouge2: 0.2011
Rougel: 0.3064
Rougelsum: 0.3064
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
1.3824
0.43
400
1.4666
0.3995
0.2014
0.3061
0.3064
1.2617
0.87
800
1.3350
0.4065
0.2063
0.3113
0.3115
Framework versions
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
