Md-Z/finetuned-phi2-financial-sentiment-analysis

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finetuned-phi2-financial-sentiment-analysis

This model is a fine-tuned version of microsoft/phi-2 on the FinancialPhraseBank dataset. The FinancialPhraseBank dataset is a comprehensive collection that captures the sentiments of financial news headlines from the viewpoint of a retail investor. Comprising two key columns, namely "Sentiment" and "News Headline," the dataset effectively classifies sentiments as either negative, neutral, or positive. This structured dataset serves as a valuable resource for analyzing and understanding the complex dynamics of sentiment in the domain of financial news. It achieves the following results on the evaluation set:

• —Loss: 1.4052

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: 0.0002
• —trainbatchsize: 1
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 8
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.03
• —num_epochs: 4
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.7.1
• —Transformers 4.38.0.dev0
• —Pytorch 2.0.0+cu117
• —Datasets 2.16.1
• —Tokenizers 0.15.0