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summarizer_MediQA – AI Model by Chelomo | AlphaNeural AI
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Chelomo
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summarizer_MediQA
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transformers
pytorch
tensorboard
bart
text2text-generation
generated_from_trainer
apache-2.0
endpoints_compatible
us
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summarizer_MediQA
This model is a fine-tuned version of
facebook/bart-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.9087
Rouge1: 0.1757
Rouge2: 0.0665
Rougel: 0.1487
Rougelsum: 0.1548
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: 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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
No log
1.0
56
1.9335
0.1799
0.0713
0.1555
0.1613
No log
2.0
112
1.9155
0.1727
0.0672
0.1489
0.1535
No log
3.0
168
1.9087
0.1757
0.0665
0.1487
0.1548
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cpu
Datasets 2.9.0
Tokenizers 0.13.2
