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bert-large-cased-bn-adapter-3.17M-snli-model1 – AI Model by varun-v-rao | AlphaNeural AI
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varun-v-rao
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bert-large-cased-bn-adapter-3.17M-snli-model1
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tensorboard
generated_from_trainer
google-bert/bert-large-cased
finetune
apache-2.0
us
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bert-large-cased-bn-adapter-3.17M-snli-model1
This model is a fine-tuned version of
bert-large-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.7500
Accuracy: 0.736
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: 83
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
Accuracy
0.412
1.0
8584
0.3365
0.8770
0.3706
2.0
17168
0.3072
0.8872
0.3597
3.0
25752
0.2988
0.8888
Framework versions
Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0
