---
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_bert-base-uncased
  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_bert-base-uncased

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: 0.5398
- Accuracy: 0.8705
- F1: 0.8691
- Precision: 0.8729
- Recall: 0.8705

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9217        | 1.0   | 91   | 0.8648          | 0.6459   | 0.5998 | 0.6333    | 0.6459 |
| 0.5726        | 2.0   | 182  | 0.5369          | 0.8066   | 0.8064 | 0.8238    | 0.8066 |
| 0.3522        | 3.0   | 273  | 0.4095          | 0.8440   | 0.8415 | 0.8477    | 0.8440 |
| 0.2589        | 4.0   | 364  | 0.5367          | 0.8097   | 0.8069 | 0.8258    | 0.8097 |
| 0.2718        | 5.0   | 455  | 0.4216          | 0.8612   | 0.8621 | 0.8670    | 0.8612 |
| 0.164         | 6.0   | 546  | 0.5346          | 0.8612   | 0.8602 | 0.8616    | 0.8612 |
| 0.1075        | 7.0   | 637  | 0.5398          | 0.8705   | 0.8691 | 0.8729    | 0.8705 |
| 0.1461        | 8.0   | 728  | 0.6163          | 0.8362   | 0.8368 | 0.8442    | 0.8362 |
| 0.132         | 9.0   | 819  | 0.4933          | 0.8674   | 0.8675 | 0.8701    | 0.8674 |
| 0.1359        | 10.0  | 910  | 0.7141          | 0.8424   | 0.8416 | 0.8489    | 0.8424 |
| 0.0971        | 11.0  | 1001 | 0.5662          | 0.8596   | 0.8578 | 0.8623    | 0.8596 |
| 0.1148        | 12.0  | 1092 | 0.5685          | 0.8612   | 0.8609 | 0.8610    | 0.8612 |


### Framework versions

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