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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: xlm-roberta-base-misogyny-sexism-tweets
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xlm-roberta-base-misogyny-sexism-tweets
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5009
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- Accuracy: 0.796
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- F1: 0.8132
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- Precision: 0.75
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- Recall: 0.888
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- Mae: 0.204
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- Tn: 352
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- Fp: 148
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- Fn: 56
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- Tp: 444
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Mae | Tn | Fp | Fn | Tp |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:---:|:--:|:---:|
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| 0.4947 | 1.0 | 1646 | 0.4683 | 0.765 | 0.7866 | 0.7205 | 0.866 | 0.235 | 332 | 168 | 67 | 433 |
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| 0.4285 | 2.0 | 3292 | 0.4514 | 0.779 | 0.8004 | 0.7298 | 0.886 | 0.221 | 336 | 164 | 57 | 443 |
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| 0.3721 | 3.0 | 4938 | 0.4430 | 0.781 | 0.8060 | 0.7234 | 0.91 | 0.219 | 326 | 174 | 45 | 455 |
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| 0.3127 | 4.0 | 6584 | 0.5009 | 0.796 | 0.8132 | 0.75 | 0.888 | 0.204 | 352 | 148 | 56 | 444 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.12.0+cu102
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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