fine-tuned-BioBART-5-epochs-1500-input-256-output – AI Model by tanatapanun | AlphaNeural AI

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tanatapanun/
fine-tuned-BioBART-5-epochs-1500-input-256-output

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text2text-generation

generated_from_trainer

GanjinZero/biobart-base

endpoints_compatible

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fine-tuned-BioBART-5-epochs-1500-input-256-output

This model is a fine-tuned version of GanjinZero/biobart-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9334
Rouge1: 0.1033
Rouge2: 0.0329
Rougel: 0.0852
Rougelsum: 0.0855
Gen Len: 26.37

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: 0.0001
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	151	1.3238	0.0708	0.0184	0.0658	0.065	12.37
No log	2.0	302	1.0363	0.1129	0.0331	0.0944	0.0938	29.38
No log	3.0	453	0.9690	0.0999	0.024	0.0813	0.082	18.88
2.6167	4.0	604	0.9406	0.1079	0.0327	0.0869	0.0871	27.93
2.6167	5.0	755	0.9334	0.1033	0.0329	0.0852	0.0855	26.37

Framework versions

Transformers 4.36.2
Pytorch 1.12.1+cu113
Datasets 2.16.1
Tokenizers 0.15.0