---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-multilingual-cased-finetuned-misogyny-sexism-out-of-sample-test-opt-EN
  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-out-of-sample-test-opt-EN

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: 0.7652
- Accuracy: 0.8803
- F1: 0.7072
- Precision: 0.6321
- Recall: 0.8026
- Mae: 0.1197

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3671        | 1.0   | 2395  | 0.3383          | 0.8489   | 0.6453 | 0.5587    | 0.7637 | 0.1511 |
| 0.3265        | 2.0   | 4790  | 0.2955          | 0.8851   | 0.6944 | 0.6665    | 0.7247 | 0.1149 |
| 0.2678        | 3.0   | 7185  | 0.4224          | 0.8481   | 0.6627 | 0.5521    | 0.8286 | 0.1519 |
| 0.2087        | 4.0   | 9580  | 0.5581          | 0.8516   | 0.6656 | 0.5599    | 0.8204 | 0.1484 |
| 0.1798        | 5.0   | 11975 | 0.5814          | 0.8726   | 0.6971 | 0.6094    | 0.8142 | 0.1274 |
| 0.1417        | 6.0   | 14370 | 0.6090          | 0.8860   | 0.7126 | 0.6525    | 0.7848 | 0.1140 |
| 0.1316        | 7.0   | 16765 | 0.5833          | 0.8899   | 0.7202 | 0.6640    | 0.7869 | 0.1101 |
| 0.1143        | 8.0   | 19160 | 0.6505          | 0.8885   | 0.7189 | 0.6580    | 0.7923 | 0.1115 |
| 0.1081        | 9.0   | 21555 | 0.6128          | 0.8978   | 0.7325 | 0.6926    | 0.7773 | 0.1022 |
| 0.1034        | 10.0  | 23950 | 0.7652          | 0.8803   | 0.7072 | 0.6321    | 0.8026 | 0.1197 |


### Framework versions

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