lmind_hotpot_train8000_eval7405_v1_reciteonly_qa_meta-llama_Llama-2-7b-hf_5e-5_lora2

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa dataset. It achieves the following results on the evaluation set:

• Loss: 1.6390
• Accuracy: 0.7019

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: 5e-05
• 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: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0487	1.0	250	1.0322	0.7170
0.997	2.0	500	1.0206	0.7177
0.9702	3.0	750	1.0203	0.7178
0.9298	4.0	1000	1.0288	0.7173
0.8959	5.0	1250	1.0434	0.7166
0.8507	6.0	1500	1.0611	0.7156
0.8061	7.0	1750	1.0810	0.7147
0.7634	8.0	2000	1.1032	0.7137
0.7235	9.0	2250	1.1337	0.7126
0.6842	10.0	2500	1.1706	0.7117
0.6319	11.0	2750	1.2172	0.7103
0.5942	12.0	3000	1.2546	0.7094
0.5557	13.0	3250	1.2890	0.7081
0.5202	14.0	3500	1.3411	0.7073
0.4803	15.0	3750	1.3868	0.7061
0.4495	16.0	4000	1.4516	0.7050
0.4086	17.0	4250	1.4881	0.7040
0.3712	18.0	4500	1.5444	0.7033
0.339	19.0	4750	1.5931	0.7026
0.3129	20.0	5000	1.6390	0.7019

Framework versions

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