This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
Loss: 0.6764
Rewards/chosen: 0.0307
Rewards/rejected: -0.0060
Rewards/accuracies: 0.7173
Rewards/margins: 0.0367
Logps/rejected: -867.9213
Logps/chosen: -604.5544
Logits/rejected: -0.5562
Logits/chosen: 0.0445
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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
