This model is a fine-tuned version of google/gemma-2-9b-it on the jz666/gemma2-ultrafeedback-ppl-split-10 dataset. It achieves the following results on the evaluation set:

Loss: 2.7053
Rewards/chosen: -19.9733
Rewards/rejected: -25.3604
Rewards/accuracies: 0.7746
Rewards/margins: 5.3871
Logps/rejected: -2.5360
Logps/chosen: -1.9973
Logits/rejected: -14.2055
Logits/chosen: -14.1364

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: 8e-07
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 16
total_train_batch_size: 128
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
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
2.7717	0.8724	400	2.7137	-19.8216	-25.1579	0.7746	5.3363	-2.5158	-1.9822	-14.1319	-14.0744

Framework versions

Transformers 4.44.2
Pytorch 2.7.0+cu128
Datasets 2.18.0
Tokenizers 0.19.1

jz666/gemma-2-9b-it-simpo-split-10-train_filtered_full

gemma-2-9b-it-simpo-split-10-train_filtered_full

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jz666/
gemma-2-9b-it-simpo-split-10-train_filtered_full