medical_jargons_simplifier – AI Model by nadika | AlphaNeural AI

You can deploy this model and start earning money today!

nadika/
medical_jargons_simplifier

like

0

text2text-generation

generated_from_trainer

luqh/ClinicalT5-base

text-generation-inference

endpoints_compatible

Views

No views yet

medical_jargons_simplifier

This model is a fine-tuned version of luqh/ClinicalT5-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4405

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
3.2542	0.2017	500	0.5136
0.5482	0.4034	1000	0.4729
0.5112	0.6051	1500	0.4599
0.5042	0.8068	2000	0.4532
0.5043	1.0085	2500	0.4488
0.5085	1.2102	3000	0.4448
0.4692	1.4119	3500	0.4432
0.495	1.6136	4000	0.4416
0.4798	1.8152	4500	0.4405

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1