69246771-a625-42d2-ac7c-5662478974f5

This model is a fine-tuned version of oopsung/llama2-7b-koNqa-test-v1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1476

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: 0.000204
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 50
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0009	1	2.8770
0.4058	0.0443	50	0.4839
0.2543	0.0887	100	0.3843
0.2117	0.1330	150	0.3515
0.2255	0.1774	200	0.3306
0.1617	0.2217	250	0.2855
0.1575	0.2661	300	0.2383
0.179	0.3104	350	0.1824
0.1444	0.3548	400	0.1612
0.1243	0.3991	450	0.1467
0.0943	0.4435	500	0.1476

Framework versions

• PEFT 0.13.2
• Transformers 4.46.0
• Pytorch 2.5.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1