---
license: apache-2.0
base_model: google/electra-small-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra-small-discriminator-zeroshot-v1.1-none
  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-small-discriminator-zeroshot-v1.1-none

This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3747
- F1 Macro: 0.4125
- F1 Micro: 0.4620
- Accuracy Balanced: 0.4701
- Accuracy: 0.4620
- Precision Macro: 0.5162
- Recall Macro: 0.4701
- Precision Micro: 0.4620
- Recall Micro: 0.4620

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 80085
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.04
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.4765        | 0.32  | 5000  | 0.5300          | 0.7326   | 0.7528   | 0.7329            | 0.7528   | 0.7322          | 0.7329       | 0.7528          | 0.7528       |
| 0.4408        | 0.65  | 10000 | 0.5099          | 0.7402   | 0.765    | 0.7359            | 0.765    | 0.7463          | 0.7359       | 0.765           | 0.765        |
| 0.4169        | 0.97  | 15000 | 0.4976          | 0.7473   | 0.7702   | 0.7439            | 0.7702   | 0.7517          | 0.7439       | 0.7702          | 0.7702       |
| 0.387         | 1.3   | 20000 | 0.4943          | 0.7525   | 0.7742   | 0.7498            | 0.7742   | 0.7559          | 0.7498       | 0.7742          | 0.7742       |
| 0.3905        | 1.62  | 25000 | 0.4931          | 0.7522   | 0.775    | 0.7484            | 0.775    | 0.7572          | 0.7484       | 0.775           | 0.775        |
| 0.4001        | 1.95  | 30000 | 0.4924          | 0.7544   | 0.7752   | 0.7524            | 0.7752   | 0.7568          | 0.7524       | 0.7752          | 0.7752       |
| 0.3995        | 2.27  | 35000 | 0.4900          | 0.7543   | 0.7758   | 0.7517            | 0.7758   | 0.7576          | 0.7517       | 0.7758          | 0.7758       |
| 0.3981        | 2.6   | 40000 | 0.4906          | 0.7529   | 0.7742   | 0.7504            | 0.7742   | 0.7558          | 0.7504       | 0.7742          | 0.7742       |
| 0.4232        | 2.92  | 45000 | 0.4904          | 0.7544   | 0.776    | 0.7516            | 0.776    | 0.7579          | 0.7516       | 0.776           | 0.776        |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3