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t5-small-finetuned-NL2ModelioMQ – AI Model by JuanCadavid | AlphaNeural AI
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JuanCadavid
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t5-small-finetuned-NL2ModelioMQ
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transformers
pytorch
tensorboard
t5
text2text-generation
generated_from_trainer
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-small-finetuned-NL2ModelioMQ
This model is a fine-tuned version of
t5-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0755
Rouge2 Precision: 0.7481
Rouge2 Recall: 0.462
Rouge2 Fmeasure: 0.5577
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge2 Precision
Rouge2 Recall
Rouge2 Fmeasure
No log
1.0
449
0.1696
0.6061
0.3886
0.4635
0.653
2.0
898
0.0933
0.7231
0.4496
0.5415
0.2028
3.0
1347
0.0755
0.7481
0.462
0.5577
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2
