llama_3_alpaca_midset_helpful

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0099

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 200

Training results

Training Loss	Epoch	Step	Validation Loss
1.6101	0.04	5	1.8019
1.5072	0.08	10	1.3098
1.156	0.12	15	1.2003
1.0047	0.16	20	1.1432
1.0703	0.2	25	1.0834
0.8951	0.24	30	1.0848
0.958	0.28	35	1.0538
1.0478	0.32	40	1.0488
0.9554	0.36	45	1.0497
0.9492	0.4	50	1.0381
0.8987	0.44	55	1.0346
1.0023	0.48	60	1.0310
0.9009	0.52	65	1.0343
1.0744	0.56	70	1.0283
1.0442	0.6	75	1.0278
0.9359	0.64	80	1.0275
0.9779	0.68	85	1.0209
0.9648	0.72	90	1.0263
0.9716	0.76	95	1.0251
0.9314	0.8	100	1.0223
0.9222	0.84	105	1.0225
0.9168	0.88	110	1.0172
0.9443	0.92	115	1.0157
0.9118	0.96	120	1.0106
0.9033	1.0	125	1.0087
0.8561	1.04	130	1.0095
0.7864	1.08	135	1.0143
0.8036	1.12	140	1.0193
0.7636	1.16	145	1.0197
0.8088	1.2	150	1.0189
0.781	1.24	155	1.0157
0.8032	1.28	160	1.0130
0.767	1.32	165	1.0116
0.7653	1.3600	170	1.0115
0.8196	1.4	175	1.0128
0.7688	1.44	180	1.0109
0.8094	1.48	185	1.0107
0.83	1.52	190	1.0110
0.7644	1.56	195	1.0103
0.8796	1.6	200	1.0099

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1