---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra-distilled-sst
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# electra-distilled-sst

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3772
- Accuracy: 0.9174

## 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: 4.854751380955516e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3762        | 1.0   | 527  | 0.2865          | 0.9083   |
| 0.2105        | 2.0   | 1054 | 0.3472          | 0.9048   |
| 0.1566        | 3.0   | 1581 | 0.3098          | 0.9243   |
| 0.1221        | 4.0   | 2108 | 0.3681          | 0.9174   |
| 0.1029        | 5.0   | 2635 | 0.3772          | 0.9174   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.19.1