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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: xlm-roberta-base
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: 0.9064
- Accuracy: 0.8334
- F1: 0.3322
- Precision: 0.2498
- Recall: 0.4961
- Mae: 0.1666
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
| 0.3869 | 1.0 | 2395 | 0.2905 | 0.8778 | 0.3528 | 0.3164 | 0.3988 | 0.1222 |
| 0.3539 | 2.0 | 4790 | 0.4143 | 0.8278 | 0.3465 | 0.2536 | 0.5467 | 0.1722 |
| 0.3124 | 3.0 | 7185 | 0.3327 | 0.8568 | 0.3583 | 0.2864 | 0.4786 | 0.1432 |
| 0.2817 | 4.0 | 9580 | 0.5621 | 0.7329 | 0.3092 | 0.1972 | 0.7160 | 0.2671 |
| 0.2651 | 5.0 | 11975 | 0.4376 | 0.8520 | 0.3607 | 0.2821 | 0.5 | 0.1480 |
| 0.2249 | 6.0 | 14370 | 0.5581 | 0.8326 | 0.3312 | 0.2485 | 0.4961 | 0.1674 |
| 0.1958 | 7.0 | 16765 | 0.6728 | 0.8382 | 0.3234 | 0.2484 | 0.4630 | 0.1618 |
| 0.1899 | 8.0 | 19160 | 0.7404 | 0.8304 | 0.3316 | 0.2471 | 0.5039 | 0.1696 |
| 0.1619 | 9.0 | 21555 | 0.8309 | 0.8461 | 0.3382 | 0.2639 | 0.4708 | 0.1539 |
| 0.1453 | 10.0 | 23950 | 0.9064 | 0.8334 | 0.3322 | 0.2498 | 0.4961 | 0.1666 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
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