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bart-cnn-samsum-finetuned – AI Model by dayaburamshetty | AlphaNeural AI
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dayaburamshetty
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bart-cnn-samsum-finetuned
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transformers
tensorboard
safetensors
bart
text2text-generation
generated_from_trainer
samsum
dayaburamshetty/bart-cnn-samsum-finetuned
finetune
mit
endpoints_compatible
us
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bart-cnn-samsum-finetuned
This model is a fine-tuned version of
dayaburamshetty/bart-cnn-samsum-finetuned
on the samsum dataset. It achieves the following results on the evaluation set:
Loss: 0.1341
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: 1e-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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
0.1191
1.0
74
0.1344
0.0974
2.0
148
0.1341
0.1043
3.0
222
0.1342
0.0875
4.0
296
0.1341
0.0767
5.0
370
0.1341
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0
