ndsanjana/bert-finetuned-twitter_sentiment_analysis

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bert-finetuned-twittersentimentanalysis

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4175
• —F1: 0.7741
• —Roc Auc: 0.8301
• —Accuracy: 0.7639

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: 3e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.46.3
• —Pytorch 2.4.1+cu121
• —Datasets 3.2.0
• —Tokenizers 0.20.3