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bert-finetuned-mrpc – AI Model by dylan12291 | AlphaNeural AI
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dylan12291
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bert-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-finetuned-mrpc
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4656
Accuracy: 0.8284
F1: 0.8776
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
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
lr_scheduler_warmup_steps: 500
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5973
1.0
459
0.5266
0.7426
0.8377
0.4304
2.0
918
0.4091
0.8113
0.8693
0.3288
3.0
1377
0.4656
0.8284
0.8776
Framework versions
Transformers 4.53.2
Pytorch 2.3.1
Datasets 4.0.0
Tokenizers 0.21.2
