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bert-sst2-sentiment – AI Model by mavinsao | AlphaNeural AI
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mavinsao
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bert-sst2-sentiment
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pytorch
bert
generated_from_trainer
text-classification
en
stanfordnlp/sst2
google-bert/bert-base-uncased
finetune
apache-2.0
us
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bert-sst2-sentiment
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2764
Accuracy: 0.9197
F1: 0.9197
Precision: 0.9201
Recall: 0.9197
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.1654
1.0
1053
0.2157
0.9243
0.9243
0.9247
0.9243
0.099
2.0
2106
0.2533
0.9197
0.9197
0.9197
0.9197
0.0779
3.0
3159
0.2764
0.9197
0.9197
0.9201
0.9197
Framework versions
Transformers 4.28.1
Pytorch 2.2.1+cu121
Datasets 3.1.0
Tokenizers 0.13.3
