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
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
3.9873	1.0	7344	3.9434	-46.0543	-47.7041	0.6473	1.6497	-4.7704	-4.6054	14.6796	14.4459

Framework versions

Transformers 4.45.2
Pytorch 2.3.0
Datasets 2.21.0
Tokenizers 0.20.2

sedrickkeh/checkpoints

model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sedrickkeh/
checkpoints