FLAN-T5-QASPER-NLP-Paper-to-Question-Generation-answer-input – AI Model by UNIST-Eunchan | AlphaNeural AI

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UNIST-Eunchan/
FLAN-T5-QASPER-NLP-Paper-to-Question-Generation-answer-input

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text2text-generation

generated_from_trainer

google/flan-t5-large

text-generation-inference

endpoints_compatible

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FLAN-T5-QASPER-NLP-Paper-to-Question-Generation-answer-input

This model is a fine-tuned version of google/flan-t5-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0746

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 184
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.99	46	39.0024
33.7249	1.99	92	18.8406
33.7249	2.98	138	5.0432
8.9783	3.97	184	0.1579
8.9783	4.97	230	0.0941
0.1833	5.96	276	0.0810
0.1833	6.95	322	0.0756
0.1047	7.95	368	0.0746
0.1047	8.94	414	0.0746
0.0995	9.93	460	0.0746

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0