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BERT-tiny-sst2 – AI Model by gokuls | AlphaNeural AI
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BERT-tiny-sst2
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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BERT-tiny-sst2
This model is a fine-tuned version of
google/bert_uncased_L-2_H-128_A-2
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.4422
Accuracy: 0.8372
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: 16
eval_batch_size: 16
seed: 33
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
0.3914
1.0
4210
0.4383
0.8211
0.2577
2.0
8420
0.4422
0.8372
0.212
3.0
12630
0.5460
0.8085
0.1862
4.0
16840
0.5885
0.8245
0.1671
5.0
21050
0.7159
0.8096
Framework versions
Transformers 4.22.1
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.12.1
