This model is a fine-tuned version of decapoda-research/Adrastea-7b-v1.0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6086
Rewards/chosen: 0.1339
Rewards/rejected: -0.0905
Rewards/accuracies: 0.6976
Rewards/margins: 0.2244
Logps/rejected: -260.8578
Logps/chosen: -297.0598
Logits/rejected: -3.6473
Logits/chosen: -3.5958

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-07
train_batch_size: 2
eval_batch_size: 4
seed: 420
distributed_type: multi-GPU
num_devices: 3
gradient_accumulation_steps: 32
total_train_batch_size: 192
total_eval_batch_size: 12
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6101	1.0	322	0.6086	0.1339	-0.0905	0.6976	0.2244	-260.8578	-297.0598	-3.6473	-3.5958

Framework versions

Transformers 4.35.0
Pytorch 2.1.1+cu121
Datasets 2.14.6
Tokenizers 0.14.1

decapoda-research/Adrastea-7b-v1.0-dpo-lora

zephyr-7b-dpo-lora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

decapoda-research/
Adrastea-7b-v1.0-dpo-lora