llama-2-nsmc

This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset.

Model description

한국어 영화 리뷰 데이터셋(NSMC)을 해결하는 모델이 되도록 미세튜닝 한국 영화 리뷰의 긍정 또는 부정을 판단하는 모델을 학습

Intended uses & limitations

More information needed

Training and evaluation data

TrainOutput(global_step=363, training_loss=0.9200148254058249, metrics={'train_runtime': 1447.7436, 'train_samples_per_second': 2.072, 'train_steps_per_second': 1.036, 'total_flos': 1.4780753208410112e+16, 'train_loss': 0.9200148254058249, 'epoch': 0.24})

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 2
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0