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hangman-bert-base – AI Model by vaibhav9 | AlphaNeural AI
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vaibhav9
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hangman-bert-base
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transformers
pytorch
bert
fill-mask
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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hangman-bert-base
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: nan
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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
1.1098
1.0
2609
nan
1.0599
2.0
5218
nan
1.0219
3.0
7827
nan
Framework versions
Transformers 4.33.2
Pytorch 2.0.1
Datasets 2.14.5
Tokenizers 0.13.3
