---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: Electra-Thesis-NonKFold
  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-Thesis-NonKFold

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: 1.4914
- F1: 0.6390
- Recall: 0.6390
- Accuracy: 0.6390

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Recall | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
| 1.6531        | 1.0   | 1446  | 1.3688          | 0.5851 | 0.5851 | 0.5851   |
| 1.2404        | 2.0   | 2892  | 1.2674          | 0.6230 | 0.6230 | 0.6230   |
| 1.0544        | 3.0   | 4338  | 1.2389          | 0.6322 | 0.6322 | 0.6322   |
| 0.9189        | 4.0   | 5784  | 1.2293          | 0.6376 | 0.6376 | 0.6376   |
| 0.8034        | 5.0   | 7230  | 1.3130          | 0.6384 | 0.6384 | 0.6384   |
| 0.7351        | 6.0   | 8676  | 1.3463          | 0.6390 | 0.6390 | 0.6390   |
| 0.6481        | 7.0   | 10122 | 1.3858          | 0.6385 | 0.6385 | 0.6385   |
| 0.5885        | 8.0   | 11568 | 1.4379          | 0.6372 | 0.6372 | 0.6372   |
| 0.5533        | 9.0   | 13014 | 1.4792          | 0.6344 | 0.6344 | 0.6344   |
| 0.5285        | 10.0  | 14460 | 1.4914          | 0.6390 | 0.6390 | 0.6390   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3