---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Hate-Speech-Detection-mpnet-basev2
  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. -->

# Hate-Speech-Detection-mpnet-basev2

This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4546
- Accuracy: 0.9320
- F1: 0.9317

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 225  | 0.2916          | 0.8952   | 0.9027 |
| No log        | 2.0   | 450  | 0.2543          | 0.9153   | 0.9156 |
| 0.2816        | 3.0   | 675  | 0.2853          | 0.9164   | 0.9158 |
| 0.2816        | 4.0   | 900  | 0.3623          | 0.9197   | 0.9221 |
| 0.0831        | 5.0   | 1125 | 0.4164          | 0.9186   | 0.9207 |
| 0.0831        | 6.0   | 1350 | 0.4079          | 0.9208   | 0.9198 |
| 0.0232        | 7.0   | 1575 | 0.4187          | 0.9275   | 0.9267 |
| 0.0232        | 8.0   | 1800 | 0.4831          | 0.9231   | 0.9246 |
| 0.0089        | 9.0   | 2025 | 0.4570          | 0.9298   | 0.9305 |
| 0.0089        | 10.0  | 2250 | 0.4546          | 0.9320   | 0.9317 |
| 0.0089        | 11.0  | 2475 | 0.5022          | 0.9264   | 0.9278 |
| 0.0051        | 12.0  | 2700 | 0.5734          | 0.9208   | 0.9232 |
| 0.0051        | 13.0  | 2925 | 0.5780          | 0.9186   | 0.9211 |
| 0.002         | 14.0  | 3150 | 0.5049          | 0.9287   | 0.9295 |
| 0.002         | 15.0  | 3375 | 0.5444          | 0.9231   | 0.9249 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.10.1
- Tokenizers 0.13.3