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
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: 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