---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: electra-base-discriminator-finetuned-detests-wandb24
  results: []
---

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# electra-base-discriminator-finetuned-detests-wandb24

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: 0.4457
- Accuracy: 0.7741
- F1-score: 0.6965
- Precision: 0.6879
- Recall: 0.7092
- Auc: 0.7092

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
| 0.4719        | 1.0   | 77   | 0.4698          | 0.7971   | 0.6380   | 0.7159    | 0.6199 | 0.6199 |
| 0.4737        | 2.0   | 154  | 0.4457          | 0.7741   | 0.6965   | 0.6879    | 0.7092 | 0.7092 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1