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PubMed_summarization – AI Model by mreisman | AlphaNeural AI
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mreisman
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PubMed_summarization
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transformers
tensorboard
safetensors
t5
text2text-generation
generated_from_trainer
pubmed-summarization
google-t5/t5-small
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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PubMed_summarization
This model is a fine-tuned version of
t5-small
on the pubmed-summarization dataset.
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
No log
1.0
415
2.4180
0.1351
0.0511
0.1134
0.1134
19.0
Framework versions
Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
