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idt5-base-qg-baseline-TydiQA-id – AI Model by hawalurahman | AlphaNeural AI
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idt5-base-qg-baseline-TydiQA-id
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transformers
tensorboard
safetensors
t5
text2text-generation
generated_from_trainer
muchad/idt5-base
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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idt5-base-qg-baseline-TydiQA-id
This model is a fine-tuned version of
muchad/idt5-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.4646
Rouge1: 0.4057
Rouge2: 0.2091
Rougel: 0.3995
Rougelsum: 0.3994
Bleu: 0.1497
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Bleu
3.3776
1.0
571
1.4646
0.4057
0.2091
0.3995
0.3994
0.1497
Framework versions
Transformers 4.46.3
Pytorch 2.4.0a0+f70bd71a48.nv24.06
Datasets 3.1.0
Tokenizers 0.20.3
