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sa_BERT_no_pretrain_rte – AI Model by gokuls | AlphaNeural AI | AlphaNeural AI
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sa_BERT_no_pretrain_rte
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
en
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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sa_BERT_no_pretrain_rte
This model is a fine-tuned version of
bert-base-uncased
on the GLUE RTE dataset. It achieves the following results on the evaluation set:
Loss: 0.6909
Accuracy: 0.5307
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: 96
eval_batch_size: 96
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
0.7596
1.0
26
0.6909
0.5307
0.6968
2.0
52
0.6914
0.5235
0.7026
3.0
78
0.6911
0.5307
0.6961
4.0
104
0.6928
0.5379
0.7114
5.0
130
0.6917
0.5271
0.7005
6.0
156
0.7069
0.4729
Framework versions
Transformers 4.30.2
Pytorch 1.14.0a0+410ce96
Datasets 2.12.0
Tokenizers 0.13.3
