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bert-base-uncased-finetuned-rte-run_3-2025-03-31_23-47 – AI Model by yigitkucuk | AlphaNeural AI
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yigitkucuk
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bert-base-uncased-finetuned-rte-run_3-2025-03-31_23-47
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transformers
tensorboard
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-rte-run_3-2025-03-31_23-47
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: 0.6796
Accuracy: 0.6065
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
39
0.6904
0.5271
No log
2.0
78
0.6892
0.5776
No log
3.0
117
0.6894
0.5560
No log
4.0
156
0.6692
0.5848
No log
5.0
195
0.6796
0.6065
Framework versions
Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
