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bert-base-uncased-finetuned-qnli – AI Model by anirudh21 | AlphaNeural AI | AlphaNeural AI
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anirudh21
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bert-base-uncased-finetuned-qnli
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-finetuned-qnli
This model is a fine-tuned version of
bert-base-uncased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.6268
Accuracy: 0.7917
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
63
0.5339
0.7620
No log
2.0
126
0.4728
0.7866
No log
3.0
189
0.5386
0.7847
No log
4.0
252
0.6096
0.7904
No log
5.0
315
0.6268
0.7917
Framework versions
Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.18.1
Tokenizers 0.10.3
