lmind_hotpot_train8000_eval7405_v1_qa_meta-llama_Llama-2-7b-hf_lora2

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the tyzhu/lmind_hotpot_train8000_eval7405_v1_qa dataset. It achieves the following results on the evaluation set:

• Loss: 2.8216
• Accuracy: 0.5903

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
1.7795	1.0	250	0.6075	1.8062
1.6437	2.0	500	1.8114	0.6077
1.4652	3.0	750	1.8675	0.6061
1.2631	4.0	1000	1.9843	0.6030
1.0724	5.0	1250	2.0921	0.6001
0.8917	6.0	1500	2.2463	0.5973
0.7235	7.0	1750	2.4073	0.5943
0.5997	8.0	2000	2.5738	0.5931
0.4943	9.0	2250	2.6983	0.5905
0.4381	10.0	2500	2.8216	0.5903

Framework versions

• Transformers 4.34.0
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.14.1