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finetuned-bert-mrpc – AI Model by sgugger | AlphaNeural AI
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sgugger
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finetuned-bert-mrpc
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
glue
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuned-bert-mrpc
This model is a fine-tuned version of
bert-base-cased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.4917
Accuracy: 0.8235
F1: 0.8792
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: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5382
1.0
230
0.4008
0.8456
0.8893
0.3208
2.0
460
0.4182
0.8309
0.8844
0.1587
3.0
690
0.4917
0.8235
0.8792
Framework versions
Transformers 4.9.0.dev0
Pytorch 1.8.1+cu111
Datasets 1.8.1.dev0
Tokenizers 0.10.1
