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bert-base-cased-fine-tuned-sst2 – AI Model by ckandrew04 | AlphaNeural AI
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bert-base-cased-fine-tuned-sst2
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transformers
safetensors
bert
text-classification
generated_from_trainer
nyu-mll/glue
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-cased-fine-tuned-sst2
This model is a fine-tuned version of
bert-base-cased
on nyu-mll/glue sst2 dataset. It achieves the following results on the evaluation set:
Loss: 0.4606
Accuracy: 0.9209
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1111
1.0
4210
0.3592
0.9106
0.0726
2.0
8420
0.4517
0.9106
0.0396
3.0
12630
0.4606
0.9209
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
