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finetune_BERT – AI Model by Imanbehravan | AlphaNeural AI
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Imanbehravan
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finetune_BERT
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transformers
tensorboard
safetensors
bert
question-answering
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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finetune_BERT
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0000
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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
125
0.0002
No log
2.0
250
0.0001
No log
3.0
375
0.0001
0.0899
4.0
500
0.0000
0.0899
5.0
625
0.0000
Framework versions
Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
