0 1
---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-base-finetuned-misogyny-sexism
  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-finetuned-misogyny-sexism

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: 0.0211
- Accuracy: 0.9949
- F1: 0.9948
- Precision: 0.9906
- Recall: 0.9989
- Mae: 0.0051

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3841        | 1.0   | 2778  | 0.4443          | 0.8027   | 0.7919 | 0.8030    | 0.7811 | 0.1973 |
| 0.334         | 2.0   | 5556  | 0.4946          | 0.8058   | 0.8272 | 0.7225    | 0.9674 | 0.1942 |
| 0.2995        | 3.0   | 8334  | 0.2693          | 0.8912   | 0.8951 | 0.8344    | 0.9653 | 0.1088 |
| 0.2675        | 4.0   | 11112 | 0.2575          | 0.9145   | 0.9168 | 0.8612    | 0.98   | 0.0855 |
| 0.2263        | 5.0   | 13890 | 0.1100          | 0.9611   | 0.9598 | 0.9514    | 0.9684 | 0.0389 |
| 0.2089        | 6.0   | 16668 | 0.0999          | 0.9712   | 0.9706 | 0.9524    | 0.9895 | 0.0288 |
| 0.1871        | 7.0   | 19446 | 0.0644          | 0.9782   | 0.9774 | 0.9769    | 0.9779 | 0.0218 |
| 0.1795        | 8.0   | 22224 | 0.0264          | 0.9924   | 0.9922 | 0.9865    | 0.9979 | 0.0076 |
| 0.144         | 9.0   | 25002 | 0.0231          | 0.9924   | 0.9922 | 0.9855    | 0.9989 | 0.0076 |
| 0.1296        | 10.0  | 27780 | 0.0211          | 0.9949   | 0.9948 | 0.9906    | 0.9989 | 0.0051 |


### Framework versions

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