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superglue-boolq – AI Model by ShengdingHu | AlphaNeural AI
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ShengdingHu
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superglue-boolq
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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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superglue-boolq
This model is a fine-tuned version of
t5-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2098
Accuracy: 76.7584
Average Metrics: 76.7584
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: 0.0003
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Average Metrics
No log
0.34
100
0.2293
73.2722
73.2722
No log
0.68
200
0.2098
76.7584
76.7584
Framework versions
Transformers 4.18.0
Pytorch 1.10.2+cu111
Datasets 1.17.0
Tokenizers 0.12.1
