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bert-base-cased-sst2 – AI Model by VityaVitalich | AlphaNeural AI
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VityaVitalich
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bert-base-cased-sst2
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transformers
pytorch
bert
text-classification
generated_from_trainer
sst2
google-bert/bert-base-cased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-cased-sst2
This model is a fine-tuned version of
bert-base-cased
on the sst2 dataset. It achieves the following results on the evaluation set:
Loss: 0.2103
Accuracy: 0.9140
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: 3e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2267
1.0
527
0.2103
0.9140
0.1091
2.0
1054
0.2637
0.9174
0.0722
3.0
1581
0.2673
0.9174
0.0467
4.0
2108
0.2947
0.9266
0.0298
5.0
2635
0.3344
0.9209
Framework versions
Transformers 4.34.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.0
