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bert-base-uncased-coqa – AI Model by rooftopcoder | AlphaNeural AI
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bert-base-uncased-coqa
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transformers
pytorch
tensorboard
safetensors
bert
question-answering
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-base-uncased-coqa
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: 2.8077
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: 64
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
Training results
Training Loss
Epoch
Step
Validation Loss
3.0963
1.0
3396
2.8237
2.7925
2.0
6792
2.8077
2.7639
3.0
10188
2.8077
Framework versions
Transformers 4.29.2
Pytorch 2.0.0
Datasets 2.12.0
Tokenizers 0.13.3
