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phi-2-classifier – AI Model by roborovski | AlphaNeural AI
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roborovski
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phi-2-classifier
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transformers
pytorch
bert
text-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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phi-2-classifier
This model is a fine-tuned version of
bigcode/starencoder
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4538
Accuracy: 0.875
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: 32
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3098
1.0
1485
0.3670
0.89
0.4251
2.0
2970
0.3698
0.88
0.226
3.0
4455
0.4538
0.875
Framework versions
Transformers 4.31.0.dev0
Pytorch 1.13.1
Datasets 2.13.1
Tokenizers 0.13.3
