sentiment_analysis_trainer_model

This model is a fine-tuned version of mdhugol/indonesia-bert-sentiment-classification on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.7772
• eval_accuracy: 0.7005
• eval_precision: 0.6482
• eval_recall: 0.7005
• eval_runtime: 6.8809
• eval_samples_per_second: 290.659
• eval_steps_per_second: 36.332
• 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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1