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bart-finetuned-samsum – AI Model by rajiv8197 | AlphaNeural AI
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bart-finetuned-samsum
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transformers
tensorboard
safetensors
bart
text2text-generation
generated_from_trainer
samsum
facebook/bart-large-cnn
finetune
mit
endpoints_compatible
us
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bart-finetuned-samsum
This model is a fine-tuned version of
facebook/bart-large-cnn
on the samsum dataset. It achieves the following results on the evaluation set:
Loss: 0.3112
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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
0.1492
1.0
1842
0.2984
0.0501
2.0
3684
0.3067
0.2361
2.9986
5523
0.3112
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
