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bert-base-uncased-finetuned-triviaqa – AI Model by FabianWillner | AlphaNeural AI
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FabianWillner
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bert-base-uncased-finetuned-triviaqa
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
apache-2.0
endpoints_compatible
us
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bert-base-uncased-finetuned-triviaqa
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9252
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: 2e-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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
0.9297
1.0
11195
0.9093
0.6872
2.0
22390
0.9252
Framework versions
Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
