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bart-large-cnn-dialogue-summarizer – AI Model by Mohit-Nikhade | AlphaNeural AI
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Mohit-Nikhade
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bart-large-cnn-dialogue-summarizer
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-large-cnn
finetune
mit
endpoints_compatible
us
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bart-large-cnn-dialogue-summarizer
This model is a fine-tuned version of
facebook/bart-large-cnn
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.4574
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
1.3985
0.5431
500
1.4574
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
