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bert-base-uncased-finetuned-mrpc – AI Model by hjimenez32 | AlphaNeural AI
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hjimenez32
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bert-base-uncased-finetuned-mrpc
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-finetuned-mrpc
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4968
Accuracy: 0.7819
F1: 0.8558
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: 400
eval_batch_size: 400
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
10
0.5845
0.7034
0.8197
No log
2.0
20
0.5344
0.7377
0.8336
No log
3.0
30
0.5150
0.7623
0.8463
No log
4.0
40
0.4967
0.7819
0.8524
No log
5.0
50
0.4968
0.7819
0.8558
Framework versions
Transformers 4.53.1
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
