metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: xlm-roberta-base
model-index:
- name: xlm-roberta-base-misogyny-sexism-tweets
results: []
xlm-roberta-base-misogyny-sexism-tweets
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5009
- Accuracy: 0.796
- F1: 0.8132
- Precision: 0.75
- Recall: 0.888
- Mae: 0.204
- Tn: 352
- Fp: 148
- Fn: 56
- Tp: 444
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Mae | Tn | Fp | Fn | Tp |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4947 | 1.0 | 1646 | 0.4683 | 0.765 | 0.7866 | 0.7205 | 0.866 | 0.235 | 332 | 168 | 67 | 433 |
| 0.4285 | 2.0 | 3292 | 0.4514 | 0.779 | 0.8004 | 0.7298 | 0.886 | 0.221 | 336 | 164 | 57 | 443 |
| 0.3721 | 3.0 | 4938 | 0.4430 | 0.781 | 0.8060 | 0.7234 | 0.91 | 0.219 | 326 | 174 | 45 | 455 |
| 0.3127 | 4.0 | 6584 | 0.5009 | 0.796 | 0.8132 | 0.75 | 0.888 | 0.204 | 352 | 148 | 56 | 444 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1