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mrpc_bert-base-uncased_81_v2 – AI Model by henryscheible | AlphaNeural AI
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mrpc_bert-base-uncased_81_v2
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pytorch
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mrpc_bert-base-uncased_81_v2
This model is a fine-tuned version of
bert-base-uncased
on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
Loss: 0.6390
Accuracy: 0.8088
F1: 0.8717
Combined Score: 0.8403
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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
Training results
Framework versions
Transformers 4.23.1
Pytorch 1.12.1
Datasets 2.6.1
Tokenizers 0.13.1
