gemma-7b-dpo-full-mix1-beta-0.4-epoch-3

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: 1.3044
• Rewards/chosen: -6.0191
• Rewards/rejected: -11.1290
• Rewards/accuracies: 0.75
• Rewards/margins: 5.1099
• Logps/rejected: -479.3722
• Logps/chosen: -468.4523
• Logits/rejected: 98.8291
• Logits/chosen: 104.8679

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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.2569	1.9	100	1.0775	-6.7226	-12.3440	0.7396	5.6214	-482.4095	-470.2108	99.2330	105.2899

Framework versions

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