---
library_name: transformers
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: electra-problematic-classifier-np
  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-problematic-classifier-np

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: 0.2560
- Accuracy: 0.938
- Auc: 0.977

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.6111        | 1.0   | 132  | 0.4996          | 0.924    | 0.968 |
| 0.4567        | 2.0   | 264  | 0.3629          | 0.916    | 0.973 |
| 0.3502        | 3.0   | 396  | 0.3241          | 0.88     | 0.976 |
| 0.2987        | 4.0   | 528  | 0.2722          | 0.92     | 0.977 |
| 0.2816        | 5.0   | 660  | 0.2560          | 0.938    | 0.977 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1