0 1
---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-base-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. -->

# xlm-roberta-base-misogyny-sexism-out-of-sample-test-opt-EN

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: 0.7564
- Accuracy: 0.8640
- F1: 0.6845
- Precision: 0.5877
- Recall: 0.8197
- Mae: 0.1360

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3793        | 1.0   | 2395  | 0.3475          | 0.8460   | 0.6309 | 0.5550    | 0.7309 | 0.1540 |
| 0.3471        | 2.0   | 4790  | 0.3255          | 0.8580   | 0.6526 | 0.5830    | 0.7411 | 0.1420 |
| 0.3075        | 3.0   | 7185  | 0.3426          | 0.8379   | 0.6451 | 0.5324    | 0.8183 | 0.1621 |
| 0.2634        | 4.0   | 9580  | 0.3034          | 0.8856   | 0.7112 | 0.6521    | 0.7821 | 0.1144 |
| 0.2439        | 5.0   | 11975 | 0.4210          | 0.8656   | 0.6844 | 0.5928    | 0.8094 | 0.1344 |
| 0.2212        | 6.0   | 14370 | 0.5260          | 0.8698   | 0.6904 | 0.6035    | 0.8067 | 0.1302 |
| 0.1855        | 7.0   | 16765 | 0.5626          | 0.8739   | 0.6967 | 0.6146    | 0.8040 | 0.1261 |
| 0.1666        | 8.0   | 19160 | 0.6727          | 0.8647   | 0.6834 | 0.5905    | 0.8108 | 0.1353 |
| 0.147         | 9.0   | 21555 | 0.6287          | 0.8743   | 0.6962 | 0.6163    | 0.7999 | 0.1257 |
| 0.1367        | 10.0  | 23950 | 0.7564          | 0.8640   | 0.6845 | 0.5877    | 0.8197 | 0.1360 |


### Framework versions

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