t5-end-to-end-questions-generation – AI Model by TasmiaAzmi | AlphaNeural AI

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t5-end-to-end-questions-generation

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t5-end-to-end-questions-generation

This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.2854

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
1.7656	0.43	100	1.3979
1.5042	0.86	200	1.3440
1.3992	1.3	300	1.3230
1.3654	1.73	400	1.3035
1.3329	2.16	500	1.2980
1.2613	2.59	600	1.2880
1.2684	3.02	700	1.2798
1.2107	3.45	800	1.2847
1.2081	3.89	900	1.2808
1.1707	4.32	1000	1.2881
1.1633	4.75	1100	1.2814
1.1607	5.18	1200	1.2839
1.1272	5.61	1300	1.2852
1.1266	6.05	1400	1.2838
1.1045	6.48	1500	1.2857
1.1117	6.91	1600	1.2854

Framework versions

Transformers 4.28.1
Pytorch 2.0.0
Datasets 2.12.0
Tokenizers 0.11.0