teamtrack-ai

This model is a fine-tuned version of TheBloke/OpenHermes-2-Mistral-7B-GPTQ on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6303
• Rewards/chosen: -0.0503
• Rewards/rejected: -0.1912
• Rewards/accuracies: 0.875
• Rewards/margins: 0.1409
• Logps/rejected: -190.9696
• Logps/chosen: -89.6439
• Logits/rejected: -2.7104
• Logits/chosen: -2.8594

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: 2
• training_steps: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6859	0.01	10	0.6664	0.0030	-0.0376	0.6875	0.0406	-189.4330	-89.1108	-2.7111	-2.8122
0.6888	0.01	20	0.6478	-0.0110	-0.0944	0.875	0.0834	-190.0014	-89.2510	-2.7160	-2.8235
0.6397	0.01	30	0.6385	-0.0256	-0.1254	0.8125	0.0997	-190.3110	-89.3974	-2.7148	-2.8392
0.6501	0.02	40	0.6365	-0.0472	-0.1782	0.8125	0.1311	-190.8396	-89.6128	-2.7116	-2.8528
0.6852	0.03	50	0.6303	-0.0503	-0.1912	0.875	0.1409	-190.9696	-89.6439	-2.7104	-2.8594

Framework versions

• Transformers 4.35.2
• Pytorch 2.0.1+cu117
• Datasets 2.16.1
• Tokenizers 0.15.0