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hBERTv2_new_pretrain_48_qnli – AI Model by gokuls | AlphaNeural AI
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gokuls
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hBERTv2_new_pretrain_48_qnli
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transformers
pytorch
tensorboard
hybridbert
text-classification
generated_from_trainer
en
glue
model-index
autotrain_compatible
endpoints_compatible
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hBERTv2_new_pretrain_48_qnli
This model is a fine-tuned version of
gokuls/bert_12_layer_model_v2_complete_training_new_48
on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
Loss: 0.6635
Accuracy: 0.5967
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: 4e-05
train_batch_size: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6834
1.0
819
0.6635
0.5967
0.6634
2.0
1638
0.6696
0.5931
0.6597
3.0
2457
0.6701
0.6013
0.6607
4.0
3276
0.6780
0.5876
0.6602
5.0
4095
0.6903
0.5858
0.6577
6.0
4914
0.6712
0.5892
Framework versions
Transformers 4.29.2
Pytorch 1.14.0a0+410ce96
Datasets 2.12.0
Tokenizers 0.13.3
