---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: Electra_Hatespeech_Classifier5
  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_Hatespeech_Classifier5

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: 0.2370
- F1: 0.9484
- Accuracy: 0.9629
- Precision: 0.9540
- Recall: 0.9428

## 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: 16
- eval_batch_size: 8
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
| 0.2066        | 1.0   | 5084  | 0.2209          | 0.8904 | 0.9180   | 0.8624    | 0.9204 |
| 0.1319        | 2.0   | 10168 | 0.1719          | 0.9290 | 0.9490   | 0.9363    | 0.9218 |
| 0.0785        | 3.0   | 15252 | 0.2224          | 0.9409 | 0.9582   | 0.9617    | 0.9211 |
| 0.0365        | 4.0   | 20336 | 0.2370          | 0.9484 | 0.9629   | 0.9540    | 0.9428 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2