---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: electra-base
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# electra-base

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3373
- Accuracy: 0.8875
- Precision: 0.8919
- Recall: 0.8818
- F1: 0.8868

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3187        | 1.0   | 1074 | 0.3036          | 0.8785   | 0.8880    | 0.8663 | 0.8770 |
| 0.228         | 2.0   | 2148 | 0.3022          | 0.8861   | 0.8921    | 0.8785 | 0.8853 |
| 0.1759        | 3.0   | 3222 | 0.3373          | 0.8875   | 0.8919    | 0.8818 | 0.8868 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0