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t5-end2end-questions-generation – AI Model by Tahsin-Mayeesha | AlphaNeural AI
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t5-end2end-questions-generation
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transformers
pytorch
t5
text2text-generation
generated_from_trainer
squad_modified_for_t5_qg
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-end2end-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:
eval_loss: 1.6143
eval_runtime: 96.0898
eval_samples_per_second: 21.511
eval_steps_per_second: 5.38
epoch: 2.03
step: 600
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: 4
Framework versions
Transformers 4.20.1
Pytorch 1.12.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
