finetuning-sentiment-model-bert-10000-samples
This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2825
- Accuracy: 0.9365
- F1: 0.9363
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: 3
Training results
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for Sayantan2001/finetuning-sentiment-model-bert-10000-samples
Base model
google-bert/bert-base-uncasedDataset used to train Sayantan2001/finetuning-sentiment-model-bert-10000-samples
Evaluation results
- Accuracy on imdbtest set self-reported0.936
- F1 on imdbtest set self-reported0.936