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bart-large-xsum-samsum – AI Model by Fariha4185 | AlphaNeural AI
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bart-large-xsum-samsum
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-large-xsum
finetune
mit
endpoints_compatible
us
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bart-large-xsum-samsum
This model is a fine-tuned version of
facebook/bart-large-xsum
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.5727
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
lr_scheduler_warmup_steps: 500
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
1.4126
0.5431
500
1.5727
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
