metadata
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-hate
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: twitter-roberta-base-hate_69
results: []
twitter-roberta-base-hate_69
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-hate on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3841
- F1-score: 0.8519
- Accuracy: 0.8531
- Precision: 0.8508
- Recall: 0.8544
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 69
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 1.0 | 180 | 0.3803 | 0.8198 | 0.8217 | 0.8189 | 0.8212 |
No log | 2.0 | 360 | 0.3648 | 0.8346 | 0.8357 | 0.8338 | 0.8379 |
0.3622 | 3.0 | 540 | 0.3787 | 0.8529 | 0.8531 | 0.8557 | 0.8603 |
0.3622 | 4.0 | 720 | 0.3777 | 0.8408 | 0.8427 | 0.8401 | 0.8417 |
0.3622 | 5.0 | 900 | 0.3768 | 0.8554 | 0.8566 | 0.8542 | 0.8575 |
0.2436 | 6.0 | 1080 | 0.3841 | 0.8519 | 0.8531 | 0.8508 | 0.8544 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0