t5-questions-generation – AI Model by Bilkies | AlphaNeural AI

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Bilkies/
t5-questions-generation

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text2text-generation

generated_from_trainer

squad_modified_for_t5_qg

text-generation-inference

endpoints_compatible

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t5-questions-generation

This model is a fine-tuned version of t5-base on the squad_modified_for_t5_qg dataset. It achieves the following results on the evaluation set:

Loss: 1.5678

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss
2.584	0.34	100	1.9108
1.9664	0.68	200	1.7275
1.842	1.02	300	1.6641
1.7417	1.35	400	1.6368
1.713	1.69	500	1.6219
1.6899	2.03	600	1.6046
1.6302	2.37	700	1.5961
1.6259	2.71	800	1.5946
1.6107	3.05	900	1.5879
1.5689	3.39	1000	1.5865
1.5688	3.73	1100	1.5722
1.5519	4.06	1200	1.5792
1.5343	4.4	1300	1.5737
1.5214	4.74	1400	1.5745
1.5169	5.08	1500	1.5736
1.4954	5.42	1600	1.5730
1.4827	5.76	1700	1.5680
1.5015	6.1	1800	1.5701
1.4769	6.44	1900	1.5732
1.4765	6.77	2000	1.5678

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2