klue-bert-finetuned-nsmc

This model is a fine-tuned version of klue/bert-base on the nsmc dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.2402
• eval_accuracy: 0.9029
• eval_f1: 0.9029
• eval_runtime: 343.6707
• eval_samples_per_second: 145.488
• eval_steps_per_second: 4.548
• epoch: 1.0
• step: 4688

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Framework versions

• Transformers 4.13.0
• Pytorch 1.13.1+cu116
• Datasets 2.8.0
• Tokenizers 0.10.3