Auditor Review Sentiment Model This model has been finetuned from the proprietary version of FinBERT trained internally using demo.org proprietary dataset of auditor evaluation of sentiment. FinBERT is a BERT model pre trained on a large corpora of financial texts. The purpose is to enhance financial NLP research and practice in the financial domain, hoping that financial practitioners and researchers can benefit from this model without the necessity of the significant computational resources required to train the model. Training Data This model was fine tuned using Autotrain from the demo org/auditor review review dataset. Model Status This model is currently being evaluated in development until the end of the quarter. Based on the results, it may be elevated to production. Training hyperparameters The following hyperparameters were used during training: learning rate: 0.0002 train batch size: 16 eval batch size: 8 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 4 mixed precision training: Native AMP Model Trained Using AutoTrain Problem type: Multi class Classification Model ID: 1167143226 CO2 Emissions (in grams): 3.1657716…
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