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bert-wnli-lora-ep5-lr0p0002-bs16-r8-a16-2025-06-17-1530 – AI Model by ekiprop | AlphaNeural AI
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ekiprop
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bert-wnli-lora-ep5-lr0p0002-bs16-r8-a16-2025-06-17-1530
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peft
safetensors
generated_from_trainer
google-bert/bert-base-uncased
adapter
apache-2.0
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bert-wnli-lora-ep5-lr0p0002-bs16-r8-a16-2025-06-17-1530
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: 0.6927
Accuracy: 0.4366
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: 0.0002
train_batch_size: 16
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
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.711
1.0
40
0.7050
0.5634
0.7175
2.0
80
0.6870
0.6197
0.7138
3.0
120
0.6945
0.4507
0.6959
4.0
160
0.6917
0.5634
0.7025
5.0
200
0.6927
0.4366
Framework versions
PEFT 0.15.2
Transformers 4.52.4
Pytorch 2.7.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1
