| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: twitter-roberta-base-efl-hateval |
| | 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. --> |
| |
|
| | # twitter-roberta-base-efl-hateval |
| |
|
| | This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2021-124m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m) on the HatEval dataset. |
| | It achieves the following results on the evaluation set: |
| | - Accuracy: 0.7913 |
| | - F1: 0.7899 |
| | - Loss: 0.3683 |
| |
|
| | ## 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: 1e-06 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | |
| | |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:| |
| | | 0.5392 | 1.0 | 211 | 0.7 | 0.6999 | 0.4048 | |
| | | 0.3725 | 2.0 | 422 | 0.759 | 0.7584 | 0.3489 | |
| | | 0.3158 | 3.0 | 633 | 0.7613 | 0.7570 | 0.3287 | |
| | | 0.289 | 4.0 | 844 | 0.769 | 0.7684 | 0.3307 | |
| | | 0.2716 | 5.0 | 1055 | 0.7767 | 0.7750 | 0.3241 | |
| | | 0.2575 | 6.0 | 1266 | 0.7787 | 0.7782 | 0.3272 | |
| | | 0.2441 | 7.0 | 1477 | 0.7783 | 0.7776 | 0.3258 | |
| | | 0.2363 | 8.0 | 1688 | 0.7777 | 0.7773 | 0.3316 | |
| | | 0.2262 | 9.0 | 1899 | 0.7843 | 0.7815 | 0.3150 | |
| | | 0.2191 | 10.0 | 2110 | 0.7813 | 0.7802 | 0.3241 | |
| | | 0.2112 | 11.0 | 2321 | 0.7867 | 0.7860 | 0.3276 | |
| | | 0.2047 | 12.0 | 2532 | 0.7897 | 0.7886 | 0.3266 | |
| | | 0.1973 | 13.0 | 2743 | 0.7893 | 0.7884 | 0.3299 | |
| | | 0.1897 | 14.0 | 2954 | 0.792 | 0.7907 | 0.3301 | |
| | | 0.1862 | 15.0 | 3165 | 0.794 | 0.7925 | 0.3283 | |
| | | 0.1802 | 16.0 | 3376 | 0.7907 | 0.7903 | 0.3465 | |
| | | 0.1764 | 17.0 | 3587 | 0.7937 | 0.7922 | 0.3393 | |
| | | 0.1693 | 18.0 | 3798 | 0.7903 | 0.7893 | 0.3494 | |
| | | 0.1666 | 19.0 | 4009 | 0.7943 | 0.7930 | 0.3486 | |
| | | 0.1631 | 20.0 | 4220 | 0.7927 | 0.7917 | 0.3516 | |
| | | 0.1609 | 21.0 | 4431 | 0.7907 | 0.7893 | 0.3537 | |
| | | 0.1581 | 22.0 | 4642 | 0.7913 | 0.7902 | 0.3586 | |
| | | 0.1548 | 23.0 | 4853 | 0.789 | 0.7884 | 0.3698 | |
| | | 0.1535 | 24.0 | 5064 | 0.7893 | 0.7880 | 0.3622 | |
| | | 0.1522 | 25.0 | 5275 | 0.7923 | 0.7909 | 0.3625 | |
| | | 0.15 | 26.0 | 5486 | 0.7913 | 0.7899 | 0.3632 | |
| | | 0.1479 | 27.0 | 5697 | 0.792 | 0.7909 | 0.3677 | |
| | | 0.1441 | 28.0 | 5908 | 0.792 | 0.7909 | 0.3715 | |
| | | 0.145 | 29.0 | 6119 | 0.792 | 0.7906 | 0.3681 | |
| | | 0.1432 | 30.0 | 6330 | 0.7913 | 0.7899 | 0.3683 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.0.0 |
| | - Tokenizers 0.11.6 |
| | |
