---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-multilingual-cased-finetuned-misogyny-sexism-multilingual
  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. -->

# distilbert-base-multilingual-cased-finetuned-misogyny-sexism-multilingual

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2382
- Accuracy: 0.8435
- F1: 0.7857
- Precision: 0.7689
- Recall: 0.8031
- Mae: 0.1565

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3663        | 1.0   | 2062  | 0.3696          | 0.8363   | 0.7605 | 0.7967    | 0.7274 | 0.1637 |
| 0.2937        | 2.0   | 4124  | 0.3592          | 0.8504   | 0.7891 | 0.7948    | 0.7834 | 0.1496 |
| 0.2189        | 3.0   | 6186  | 0.4189          | 0.8442   | 0.7855 | 0.7727    | 0.7987 | 0.1558 |
| 0.1418        | 4.0   | 8248  | 0.6393          | 0.8409   | 0.7863 | 0.7558    | 0.8194 | 0.1591 |
| 0.1091        | 5.0   | 10310 | 0.7583          | 0.8284   | 0.7794 | 0.7207    | 0.8486 | 0.1716 |
| 0.0901        | 6.0   | 12372 | 0.8695          | 0.8410   | 0.7836 | 0.7628    | 0.8055 | 0.1590 |
| 0.0562        | 7.0   | 14434 | 1.0722          | 0.8405   | 0.7838 | 0.7600    | 0.8092 | 0.1595 |
| 0.0444        | 8.0   | 16496 | 1.0797          | 0.8433   | 0.7804 | 0.7815    | 0.7794 | 0.1567 |
| 0.0227        | 9.0   | 18558 | 1.1605          | 0.8429   | 0.7823 | 0.7743    | 0.7906 | 0.1571 |
| 0.0131        | 10.0  | 20620 | 1.2382          | 0.8435   | 0.7857 | 0.7689    | 0.8031 | 0.1565 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.9.0+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
