---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: xlm-roberta-base
model-index:
- name: xlm-roberta-base-misogyny-sexism-indomain-mix-bal
  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. -->

# xlm-roberta-base-misogyny-sexism-indomain-mix-bal

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8259
- Accuracy: 0.826
- F1: 0.8333
- Precision: 0.7996
- Recall: 0.87
- Mae: 0.174
- Tn: 391
- Fp: 109
- Fn: 65
- Tp: 435

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mae   | Tn  | Fp  | Fn | Tp  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:---:|:--:|:---:|
| 0.2643        | 1.0   | 1603 | 0.6511          | 0.82     | 0.8269 | 0.7963    | 0.86   | 0.18  | 390 | 110 | 70 | 430 |
| 0.2004        | 2.0   | 3206 | 0.8259          | 0.826    | 0.8333 | 0.7996    | 0.87   | 0.174 | 391 | 109 | 65 | 435 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
# Multilingual_Misogyny_Detection