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

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: 0.0275
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3412        | 1.0   | 1006  | 0.4817          | 0.7744   | 0.8023 | 0.6930    | 0.9526 | 0.2256 |
| 0.2633        | 2.0   | 2012  | 0.5045          | 0.7709   | 0.8048 | 0.6813    | 0.9832 | 0.2291 |
| 0.2286        | 3.0   | 3018  | 0.2252          | 0.9256   | 0.9253 | 0.8940    | 0.9589 | 0.0744 |
| 0.2189        | 4.0   | 4024  | 0.1373          | 0.9565   | 0.9546 | 0.9576    | 0.9516 | 0.0435 |
| 0.1424        | 5.0   | 5030  | 0.1143          | 0.9742   | 0.9735 | 0.9620    | 0.9853 | 0.0258 |
| 0.1655        | 6.0   | 6036  | 0.0787          | 0.9818   | 0.9813 | 0.9711    | 0.9916 | 0.0182 |
| 0.0843        | 7.0   | 7042  | 0.0739          | 0.9833   | 0.9829 | 0.9683    | 0.9979 | 0.0167 |
| 0.081         | 8.0   | 8048  | 0.0468          | 0.9894   | 0.9891 | 0.9794    | 0.9989 | 0.0106 |
| 0.047         | 9.0   | 9054  | 0.0390          | 0.9914   | 0.9911 | 0.9834    | 0.9989 | 0.0086 |
| 0.0198        | 10.0  | 10060 | 0.0275          | 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
