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bert-large-uncased_cls_sst2 – AI Model by ghatgetanuj | AlphaNeural AI
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ghatgetanuj
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bert-large-uncased_cls_sst2
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-large-uncased_cls_sst2
This model is a fine-tuned version of
bert-large-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3787
Accuracy: 0.9255
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.2
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
433
0.4188
0.8578
0.3762
2.0
866
0.4894
0.8968
0.3253
3.0
1299
0.3313
0.9094
0.1601
4.0
1732
0.3399
0.9232
0.0744
5.0
2165
0.3787
0.9255
Framework versions
Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
