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bert-base-uncased-finetuned-jdcv-Nov16 – AI Model by aayu | AlphaNeural AI
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bert-base-uncased-finetuned-jdcv-Nov16
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transformers
pytorch
tensorboard
bert
text-generation
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-finetuned-jdcv-Nov16
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: 0.0010
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: 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: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
0.0125
1.0
2951
0.0012
0.0083
2.0
5902
0.0010
0.0073
3.0
8853
0.0010
Framework versions
Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.0
Tokenizers 0.13.2
