finetuning-sentiment-model-bank_reviews-otherbank
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on app store reviews from OCBC bank and POSB bank (Singapore). It achieves the following results on the evaluation set:
- Loss: 0.4811
- Accuracy: 0.8630
- F1: 0.6970
Model description
Data was labelled according to review stars. If stars >3, review was ranked positive. Otherwise, it is labelled as negative. We have tried 4 stars instead of 3 as app developers would deem any negativity in reviews as negative as a whole, but accuracy dropped. Further investigations will need to be run. Above 4 stars positive: https://huggingface.co/ajiayi/finetuning-sentiment-model-bank_reviews-otherbank-4insteadof3 All data (OCBC,POSB,GXS): https://huggingface.co/ajiayi/finetuning-sentiment-model-bank_reviews
Intended uses & limitations
Model was used in the following project: https://github.com/weixuanontherun/DSA3101_Group-19 It was finetuned using OCBC and POSB and tested on GXS bank reviews.
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: 2
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Tokenizers 0.15.2
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