This model is a fine-tuned version of google/gemma-2-9b-it on the cdc0b2d9-493b-4cb1-87e8-8fb1e3f4b247 dataset.
It achieves the following results on the evaluation set:
Loss: 3.9434
Rewards/chosen: -46.0543
Rewards/rejected: -47.7041
Rewards/accuracies: 0.6473
Rewards/margins: 1.6497
Logps/rejected: -4.7704
Logps/chosen: -4.6054
Logits/rejected: 14.6796
Logits/chosen: 14.4459
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: 2
seed: 42
distributed_type: multi-GPU
num_devices: 32
gradient_accumulation_steps: 2
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08