---
license: apache-2.0
tags:
- generated_from_trainer
base_model: distilbert-base-cased
model-index:
- name: distilbert-base-cased-hate-speech
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-cased-hate-speech

**Training:** The model has been trained using the script provided in the following repository https://github.com/MorenoLaQuatra/transformers-tasks-templates

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on [hate speech](https://huggingface.co/datasets/ucberkeley-dlab/measuring-hate-speech) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6837
- Mae: 1.9686

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.6857        | 1.0   | 3389  | 0.6471          | 1.9725 |
| 0.3645        | 2.0   | 6778  | 0.4359          | 1.9725 |
| 0.2266        | 3.0   | 10167 | 0.3664          | 1.9725 |
| 0.1476        | 4.0   | 13556 | 0.3253          | 1.9725 |
| 0.0992        | 5.0   | 16945 | 0.3047          | 1.9725 |
| 0.0737        | 6.0   | 20334 | 0.2869          | 1.9725 |
| 0.0537        | 7.0   | 23723 | 0.2709          | 1.9725 |
| 0.0458        | 8.0   | 27112 | 0.2667          | 1.9725 |
| 0.0313        | 9.0   | 30501 | 0.2589          | 1.9725 |
| 0.027         | 10.0  | 33890 | 0.2540          | 1.9725 |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6