electra-small-finetuned-sst2-rotten_tomatoes-distilled
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This model is a finetuned version of google/electra-small-discriminator on sst2 and rotten tomatoes dataset. It achieves the following result during training:
- Training Loss: 0.070100
- Validation Loss: 0.268334
- Accuracy: 0.935986
This is a distilled version of electra base. Big thanks to philschmid for his tutorial.
Model Details
Model Description
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- Finetuned from model [optional]: [More Information Needed]
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Uses
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Direct Use
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
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How to Get Started with the Model
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Training Details
Training Procedure
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Preprocessing [optional]
Important Note: The text data were pre-processed before being fed to the model. The pre-processing steps will be shared later.
Training Hyperparameters
- Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
The following hyperparameters were used during training:
- learning_rate: 0.0003135413256598537
- train_batch_size: 256
- eval_batch_size: 256
- warmup_ratio: 0.1
- weight_decay: 0.0005018269723538957
- seed: 39
- num_epochs: 8
Speeds, Sizes, Times [optional]
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Evaluation
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Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
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