electra-small-finetuned-sst2-rotten_tomatoes-distilled
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
- Developed by: [More Information Needed]
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- Language(s) (NLP): [More Information Needed]
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- Finetuned from model [optional]: [More Information Needed]
Model Sources [optional]
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Uses
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Procedure
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]
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
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
Citation [optional]
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Glossary [optional]
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