This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:

Loss: 1.4830

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: 2e-05
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.6483	0.4843	100	1.6259
1.4519	0.9685	200	1.4830

Framework versions

Transformers 4.51.0
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.21.4

W-61/llama-3-8b-base-sft-hh-harmless-4xh200

llama-3-8b-base-sft-hh-harmless-4xh200-batch-64-20260416-181336

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

W-61/
llama-3-8b-base-sft-hh-harmless-4xh200