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hBERTv1_data_aug_rte – AI Model by gokuls | AlphaNeural AI
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gokuls
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hBERTv1_data_aug_rte
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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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hBERTv1_data_aug_rte
This model is a fine-tuned version of
gokuls/bert_12_layer_model_v1
on the GLUE RTE dataset. It achieves the following results on the evaluation set:
Loss: 2.3280
Accuracy: 0.5199
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: 5e-05
train_batch_size: 256
eval_batch_size: 256
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2316
1.0
568
2.3280
0.5199
0.0234
2.0
1136
3.0592
0.5271
0.0106
3.0
1704
3.6972
0.5054
0.0067
4.0
2272
3.2471
0.4765
0.0051
5.0
2840
3.3428
0.5090
0.0037
6.0
3408
3.9613
0.5054
Framework versions
Transformers 4.26.1
Pytorch 1.14.0a0+410ce96
Datasets 2.10.1
Tokenizers 0.13.2
