transformers pytorch mpnet text-classification generated_from_trainer dataset:tweets_hate_speech_detection license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- tweets_hate_speech_detection
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: Hate-Speech-Detection-mpnet-basev2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweets_hate_speech_detection
      type: tweets_hate_speech_detection
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.9749726263100266
      name: Accuracy
    - type: f1
      value: 0.8029556650246304
      name: F1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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 tweets_hate_speech_detection dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0849
- Accuracy: 0.9750
- F1: 0.8030

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.1144        | 1.0   | 1599  | 0.0955          | 0.9693   | 0.7337 |
| 0.072         | 2.0   | 3198  | 0.0849          | 0.9750   | 0.8030 |
| 0.0458        | 3.0   | 4797  | 0.0841          | 0.9764   | 0.8011 |
| 0.0156        | 4.0   | 6396  | 0.1829          | 0.9689   | 0.7762 |
| 0.012         | 5.0   | 7995  | 0.1904          | 0.9745   | 0.7758 |
| 0.0157        | 6.0   | 9594  | 0.1622          | 0.9758   | 0.7914 |
| 0.0068        | 7.0   | 11193 | 0.1741          | 0.9736   | 0.8005 |


### Framework versions

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