finetuning-sentiment-hausa1

This model is a fine-tuned version of Davlan/bert-base-multilingual-cased-finetuned-hausa on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.0989
• eval_accuracy: 0.3441
• eval_f1: 0.1762
• eval_runtime: 942.2462
• eval_samples_per_second: 4.513
• eval_steps_per_second: 0.282
• step: 0

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: 0.002
• 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: 1

Framework versions

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