gemma-7b-dpo-full-mix1-beta-0.05-epoch-2

This model is a fine-tuned version of lewtun/gemma-7b-sft-full-deita-10k-v0 on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:

• Loss: 0.4897
• Rewards/chosen: -2.0476
• Rewards/rejected: -3.4508
• Rewards/accuracies: 0.7083
• Rewards/margins: 1.4032
• Logps/rejected: -520.5655
• Logps/chosen: -494.3556
• Logits/rejected: 93.1721
• Logits/chosen: 99.2168

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: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.193	1.9	100	0.4773	-2.0019	-3.4640	0.7292	1.4620	-520.8292	-493.4434	93.2355	99.2919

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.15.1