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finetuned-bert-mrpc – AI Model by jayspring | AlphaNeural AI
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jayspring
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finetuned-bert-mrpc
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
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 an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4882
Accuracy: 0.8333
F1: 0.8836
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
0.5915
1.0
230
0.4721
0.7990
0.8664
0.4183
2.0
460
0.3872
0.8358
0.8835
0.2397
3.0
690
0.4882
0.8333
0.8836
Framework versions
Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2
