finetuning-bert-base-uncased-on-sst2
This model is a fine-tuned version of bert-base-uncased on the sst2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2424
- Accuracy: 0.9266
- F1: 0.9286
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: 1
Training results
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 4
Dataset used to train Ibrahim-Alam/finetuning-bert-base-uncased-on-sst2
Evaluation results
- Accuracy on sst2validation set self-reported0.927
- F1 on sst2validation set self-reported0.929