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---
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 |