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bert-mrpc-best-model-v2 – AI Model by KutayMelih | AlphaNeural AI
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KutayMelih
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bert-mrpc-best-model-v2
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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bert-mrpc-best-model-v2
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Accuracy: 0.8701
Loss: 0.3836
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: 2.292779748224614e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Accuracy
Validation Loss
No log
1.0
115
0.7549
0.5160
No log
2.0
230
0.8505
0.3880
No log
3.0
345
0.8701
0.3836
Framework versions
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
