llama381binstruct_summarize_short

This model is a fine-tuned version of NousResearch/Meta-Llama-3.1-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 2.2429

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: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 30
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss
1.653	1.3158	25	1.3192
0.7031	2.6316	50	1.3904
0.3683	3.9474	75	1.5407
0.1658	5.2632	100	1.9100
0.0716	6.5789	125	1.9351
0.036	7.8947	150	1.9408
0.0372	9.2105	175	1.9649
0.01	10.5263	200	2.1079
0.009	11.8421	225	2.1175
0.0144	13.1579	250	2.0791
0.0064	14.4737	275	2.0624
0.0048	15.7895	300	2.1707
0.0039	17.1053	325	2.0981
0.0026	18.4211	350	2.1469
0.0021	19.7368	375	2.1868
0.0021	21.0526	400	2.2096
0.0018	22.3684	425	2.2259
0.0017	23.6842	450	2.2357
0.0016	25.0	475	2.2411
0.0019	26.3158	500	2.2429

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1