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bert-base-uncased-rte – AI Model by JeremiahZ | AlphaNeural AI
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JeremiahZ
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bert-base-uncased-rte
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transformers
pytorch
tensorboard
safetensors
bert
text-classification
generated_from_trainer
en
glue
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-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: 0.6972
Accuracy: 0.6895
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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
156
0.6537
0.6318
No log
2.0
312
0.6383
0.6534
No log
3.0
468
0.6972
0.6895
Framework versions
Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1
