nsmc_roberta_base_model

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

• Loss: 0.2570
• Accuracy: 0.9117
• F1: 0.9117

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2501	1.0	2344	0.2306	0.9072	0.9072
0.1805	2.0	4688	0.2306	0.9112	0.9112
0.1313	3.0	7032	0.2570	0.9117	0.9117

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3