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

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4180
- Accuracy: 0.8768
- F1: 0.8767
- Precision: 0.8766
- Recall: 0.8768

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.955         | 1.0   | 91   | 0.8849          | 0.6349   | 0.5849 | 0.6173    | 0.6349 |
| 0.4845        | 2.0   | 182  | 0.4777          | 0.8237   | 0.8221 | 0.8271    | 0.8237 |
| 0.3434        | 3.0   | 273  | 0.3821          | 0.8580   | 0.8579 | 0.8598    | 0.8580 |
| 0.2683        | 4.0   | 364  | 0.5158          | 0.8237   | 0.8213 | 0.8362    | 0.8237 |
| 0.1675        | 5.0   | 455  | 0.3875          | 0.8643   | 0.8633 | 0.8651    | 0.8643 |
| 0.1788        | 6.0   | 546  | 0.4180          | 0.8768   | 0.8767 | 0.8766    | 0.8768 |
| 0.1669        | 7.0   | 637  | 0.4189          | 0.8768   | 0.8754 | 0.8775    | 0.8768 |
| 0.1103        | 8.0   | 728  | 0.5338          | 0.8534   | 0.8542 | 0.8569    | 0.8534 |
| 0.1597        | 9.0   | 819  | 0.4306          | 0.8674   | 0.8674 | 0.8676    | 0.8674 |
| 0.1443        | 10.0  | 910  | 0.6446          | 0.8580   | 0.8574 | 0.8580    | 0.8580 |
| 0.1012        | 11.0  | 1001 | 0.5104          | 0.8534   | 0.8535 | 0.8541    | 0.8534 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1