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bart-large-cnn-small-billsum-5epochs – AI Model by bheshaj | AlphaNeural AI
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bheshaj
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bart-large-cnn-small-billsum-5epochs
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transformers
pytorch
bart
text2text-generation
generated_from_trainer
billsum
mit
model-index
endpoints_compatible
us
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bart-large-cnn-small-billsum-5epochs
This model is a fine-tuned version of
facebook/bart-large-cnn
on the billsum dataset. It achieves the following results on the evaluation set:
Loss: 1.7206
Rouge1: 0.5406
Rouge2: 0.312
Rougel: 0.3945
Rougelsum: 0.4566
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: 3.373e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
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: 16
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
2.3723
1.33
16
1.8534
0.5204
0.299
0.3893
0.4441
1.6579
2.67
32
1.7208
0.5427
0.3143
0.3915
0.459
1.2397
4.0
48
1.7206
0.5406
0.312
0.3945
0.4566
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2
