This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:

Loss: 61.0152
Rewards/chosen: -0.4988
Rewards/rejected: -0.6909
Rewards/accuracies: 0.8021
Rewards/margins: 0.1921
Logps/rejected: -15.3755
Logps/chosen: -11.4268
Logits/rejected: 99.7522
Logits/chosen: 99.5411

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

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
54.5261	1.8957	100	60.8626	-0.5007	-0.6906	0.8021	0.1899	-15.3697	-11.4648	99.7591	99.5497

Framework versions

Transformers 4.40.1
Pytorch 2.1.2+cu121
Datasets 2.19.0
Tokenizers 0.19.1

chrlu/zephyr-7b-gemma-ipo

zephyr-7b-gemma-ipo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

chrlu/
zephyr-7b-gemma-ipo