This model is a fine-tuned version of ale-bay/zephyr-2b-gemma-sft on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:

Loss: 0.5950
Rewards/chosen: 0.2219
Rewards/rejected: -0.0437
Rewards/accuracies: 0.7188
Rewards/margins: 0.2656
Logps/rejected: -363.9149
Logps/chosen: -363.8262
Logits/rejected: -15.9487
Logits/chosen: -16.5867

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
0.5725	1.8957	100	0.5960	0.2261	-0.0336	0.7188	0.2597	-363.7130	-363.7419	-15.9487	-16.5860

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

ale-bay/zephyr-2b-gemma-sft-dpo

zephyr-2b-gemma-sft-dpo

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ale-bay/
zephyr-2b-gemma-sft-dpo