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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-indomain-mix-bal
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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-indomain-mix-bal
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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: 0.6715
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- Accuracy: 0.802
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- F1: 0.7735
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- Precision: 0.9037
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- Recall: 0.676
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- Mae: 0.198
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- Tn: 464
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- Fp: 36
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- Fn: 162
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- Tp: 338
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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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| 0.3727 | 1.0 | 2714 | 0.6816 | 0.735 | 0.6683 | 0.8930 | 0.534 | 0.265 | 468 | 32 | 233 | 267 |
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| 0.3257 | 2.0 | 5428 | 0.6787 | 0.753 | 0.6893 | 0.9288 | 0.548 | 0.247 | 479 | 21 | 226 | 274 |
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| 0.2785 | 3.0 | 8142 | 0.5640 | 0.779 | 0.7397 | 0.8997 | 0.628 | 0.221 | 465 | 35 | 186 | 314 |
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| 0.25 | 4.0 | 10856 | 0.6715 | 0.802 | 0.7735 | 0.9037 | 0.676 | 0.198 | 464 | 36 | 162 | 338 |
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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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