---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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: 0.6715
- Accuracy: 0.802
- F1: 0.7735
- Precision: 0.9037
- Recall: 0.676
- Mae: 0.198
- Tn: 464
- Fp: 36
- Fn: 162
- Tp: 338

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae   | Tn  | Fp | Fn  | Tp  |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:--:|:---:|:---:|
| 0.3727        | 1.0   | 2714  | 0.6816          | 0.735    | 0.6683 | 0.8930    | 0.534  | 0.265 | 468 | 32 | 233 | 267 |
| 0.3257        | 2.0   | 5428  | 0.6787          | 0.753    | 0.6893 | 0.9288    | 0.548  | 0.247 | 479 | 21 | 226 | 274 |
| 0.2785        | 3.0   | 8142  | 0.5640          | 0.779    | 0.7397 | 0.8997    | 0.628  | 0.221 | 465 | 35 | 186 | 314 |
| 0.25          | 4.0   | 10856 | 0.6715          | 0.802    | 0.7735 | 0.9037    | 0.676  | 0.198 | 464 | 36 | 162 | 338 |


### Framework versions

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