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bert_pretrain – AI Model by baveshchowdary | AlphaNeural AI
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baveshchowdary
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bert_pretrain
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transformers
tensorboard
safetensors
bert
text-generation
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert_pretrain
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: 6.4613
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: 0.0003
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
7.7021
0.55
100
6.4613
Framework versions
Transformers 4.36.0
Pytorch 2.1.2+cu121
Datasets 2.18.0
Tokenizers 0.15.1
