coderSounak/finetuning-sentiment-model-bert-multilingual

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finetuning-sentiment-model-bert-multilingual

This model is a fine-tuned version of QCRI/bert-base-multilingual-cased-pos-english on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 2.9412
• —Accuracy: 0.6624
• —F1: 0.6624
• —Precision: 0.6624
• —Recall: 0.6624

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: 2e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.24.0
• —Pytorch 1.12.1+cu113
• —Datasets 2.6.1
• —Tokenizers 0.13.2