Hate-speech-CNERG_bert-base-uncased-hatexplain-rationale-two-finetuned-lora-tweet_eval_irony
This model is a fine-tuned version of Hate-speech-CNERG/bert-base-uncased-hatexplain-rationale-two on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.6513
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
accuracy | train_loss | epoch |
---|---|---|
0.4932 | None | 0 |
0.6105 | 0.6865 | 0 |
0.5979 | 0.6589 | 1 |
0.6136 | 0.6218 | 2 |
0.6115 | 0.5979 | 3 |
0.6272 | 0.5751 | 4 |
0.6283 | 0.5581 | 5 |
0.6366 | 0.5483 | 6 |
0.6513 | 0.5348 | 7 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2
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Evaluation results
- accuracy on tweet_evalvalidation set self-reported0.651