---
datasets:
- sst2
- rotten_tomatoes
language:
- en
metrics:
- accuracy
---

# electra-small-finetuned-sst2-rotten_tomatoes-distilled

<!-- Provide a quick summary of what the model is/does. -->

This model is a finetuned version of [google/electra-small-discriminator](https://huggingface.co/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](https://www.philschmid.de/knowledge-distillation-bert-transformers).

## Model Details

### Model Description

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- **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

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### 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

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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 

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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


## Citation [optional]

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## Glossary [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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