This model is a fine-tuned version of google/gemma-2-9b-it on the jz666/gemma2-ultrafeedback-ppl-split dataset.
It achieves the following results on the evaluation set:
Loss: 3.9708
Rewards/chosen: -8.2674
Rewards/rejected: -9.9615
Rewards/accuracies: 0.7049
Rewards/margins: 1.6941
Logps/rejected: -0.9961
Logps/chosen: -0.8267
Logits/rejected: -9.8184
Logits/chosen: -10.0914
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
