transformers pytorch safetensors electra text-classification generated_from_trainer en dataset:glue base_model:google/electra-small-discriminator base_model:finetune:google/electra-small-discriminator license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/electra-small-discriminator
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- matthews_correlation
tags:
- generated_from_trainer
widget:
- text: The cat sat on the mat.
  example_title: Correct grammatical sentence
- text: Me and my friend going to the store.
  example_title: Incorrect subject-verb agreement
- text: I ain't got no money.
  example_title: Incorrect verb conjugation and double negative
- text: She don't like pizza no more.
  example_title: Incorrect verb conjugation and double negative
- text: They is arriving tomorrow.
  example_title: Incorrect verb conjugation
model-index:
- name: electra-small-discriminator-CoLA
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.5510400717227824
      name: Matthews Correlation
---


# electra-small-discriminator-CoLA

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4403
- Matthews Correlation: 0.5510

## Model description

trying to optimize accuracy/speed:

```json
{
    "epoch": 8.0,
    "eval_loss": 0.4402828514575958,
    "eval_matthews_correlation": 0.5510400717227824,
    "eval_runtime": 0.9341,
    "eval_samples": 1043,
    "eval_samples_per_second": 1116.545,
    "eval_steps_per_second": 70.654
}

```

## 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: 8e-05
- train_batch_size: 512
- eval_batch_size: 16
- seed: 32754
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 8.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6139        | 1.0   | 17   | 0.5997          | 0.0                  |
| 0.5315        | 2.0   | 34   | 0.4890          | 0.5154               |
| 0.4244        | 3.0   | 51   | 0.4469          | 0.5433               |
| 0.3568        | 4.0   | 68   | 0.4403          | 0.5510               |
| 0.319         | 5.0   | 85   | 0.4517          | 0.5654               |
| 0.2887        | 6.0   | 102  | 0.4656          | 0.5728               |
| 0.2771        | 7.0   | 119  | 0.4558          | 0.5883               |
| 0.2729        | 8.0   | 136  | 0.4569          | 0.5858               |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1
