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medicalSummarizer – AI Model by ayush0205 | AlphaNeural AI
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ayush0205
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medicalSummarizer
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transformers
safetensors
t5
text2text-generation
generated_from_trainer
google-t5/t5-small
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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medicalSummarizer
This model is a fine-tuned version of
t5-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9779
Rouge1: 21.6093
Rouge2: 12.601
Rougel: 19.1461
Rougelsum: 20.6328
Gen Len: 19.0
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
1.2835
1.0
865
0.9779
21.6093
12.601
19.1461
20.6328
19.0
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3
