BioBart_Large_Dialouge_Summarization_taskA – AI Model by Care4langGW | AlphaNeural AI

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Care4langGW/
BioBart_Large_Dialouge_Summarization_taskA

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text2text-generation

MEDIQA-Chat-2023-taskA

endpoints_compatible

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BioBart_Large_Dialouge_Summarization_taskA

This model is a fine-tuned version of GanjinZero/biobart-large on the Task A-Short Dialogue2Note Summarization dataset

It achieves the following results on the evaluation set:

Loss: 2.7487
Rouge1: 28.7953
Rouge2: 13.7224
Rougel: 27.8491
Rougelsum: 28.6028
Gen Len: 19.34

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
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	1842	2.739522	29.7742	15.4000	29.0754	29.706200	19.5600
No log	2.0	3684	2.705775	28.6469	13.7595	27.7582	28.486700	19.3700
No log	3.0	5526	2.748785	28.7953	13.7224	27.8491	28.602800	19.3400

Framework versions

Transformers 4.26.1
datasets 2.10.1
tokenizers 0.13.2