bert-base-uncased-semeval2014
This model is a fine-tuned version of bert-base-uncased on the Yaxin/SemEval2014Task4Raw All dataset. It achieves the following results on the evaluation set:
- Loss: 0.7027
- Accuracy: 0.8396
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0
Training results
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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Dataset used to train StevenLimcorn/bert-base-uncased-semeval2014
Evaluation results
- Accuracy on Yaxin/SemEval2014Task4Raw Allvalidation set self-reported0.840