everyl12/crisis_sentiment_roberta

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crisissentimentroberta

This model is a fine-tuned version of finiteautomata/bertweet-base-sentiment-analysis on an unknown dataset. It achieves the following results on the testing set:

• —Accuracy: 0.83
• —Macro accuracy: 0.76
• —Weighted accuracy: 0.83

Model description

1. 1.Negative
2. 2.Positive
3. 3.Neutral

Sentiment classification using 9,300 tweets of the Flint Water Crisis

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
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 15

Training results

Framework versions

• —Transformers 4.23.0.dev0
• —Pytorch 1.13.0.dev20220917+cu117
• —Datasets 2.4.0
• —Tokenizers 0.12.1