---
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: []
language:
- en
pipeline_tag: zero-shot-classification
---

<!-- 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

|Datasets|mnli_m|mnli_mm|fevernli|anli_r1|anli_r2|anli_r3|wanli|lingnli|wellformedquery|rottentomatoes|amazonpolarity|imdb|yelpreviews|hatexplain|massive|banking77|emotiondair|emocontext|empathetic|agnews|yahootopics|biasframes_sex|biasframes_offensive|biasframes_intent|financialphrasebank|appreviews|hateoffensive|trueteacher|spam|wikitoxic_toxicaggregated|wikitoxic_obscene|wikitoxic_identityhate|wikitoxic_threat|wikitoxic_insult|manifesto|capsotu|
| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|Accuracy|0.853|0.861|0.838|0.583|0.592|0.588|0.709|0.787|0.603|0.75|0.863|0.808|0.879|0.432|0.497|0.391|0.546|0.607|0.234|0.801|0.562|0.77|0.639|0.628|0.629|0.861|0.37|0.502|0.814|0.744|0.798|0.786|0.767|0.778|0.096|0.462|
|Inference text/sec (A100, batch=64)|4180.0|4161.0|2824.0|3233.0|3243.0|3239.0|4494.0|4288.0|5222.0|4396.0|2563.0|888.0|1035.0|4326.0|5447.0|5221.0|4871.0|4971.0|2852.0|3946.0|1585.0|4274.0|4097.0|4109.0|4229.0|3468.0|4476.0|1198.0|4514.0|1360.0|1267.0|1287.0|1232.0|1314.0|3936.0|4116.0|


## 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