tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
- f1 | |
- precision | |
- recall | |
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment | |
model-index: | |
- name: finetuned_twitter_targeted_insult_roberta | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# finetuned_twitter_targeted_insult_roberta | |
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.7333 | |
- Accuracy: 0.7193 | |
- F1: 0.7248 | |
- Precision: 0.7140 | |
- Recall: 0.7360 | |
## 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: 5 | |
### Training results | |
### Framework versions | |
- Transformers 4.24.0 | |
- Pytorch 1.12.1+cu113 | |
- Datasets 2.6.1 | |
- Tokenizers 0.13.2 | |