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model-hf-vizwiz-bert-uncased – AI Model by nanom | AlphaNeural AI
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nanom
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model-hf-vizwiz-bert-uncased
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transformers
pytorch
bert
fill-mask
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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bert_adaptation_vizwi
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: 1.2115
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.6267
1.0
411
1.3774
1.3601
2.0
822
1.3225
1.2577
3.0
1233
1.2261
1.2343
4.0
1644
1.2729
1.1936
5.0
2055
1.2580
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3
