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Bert-Base-Uncased-Pretrained – AI Model by dewanshsinghchandel | AlphaNeural AI
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Bert-Base-Uncased-Pretrained
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transformers
tensorboard
safetensors
bert
fill-mask
generated_from_trainer
autotrain_compatible
endpoints_compatible
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Bert-Base-Uncased-Pretrained
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 7.1925
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: 5e-05
train_batch_size: 5
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 40
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
50
7.2354
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
