--- library_name: transformers base_model: W-61/llama-3-8b-base-sft-hh-helpful-4xh200 tags: - alignment-handbook - new-dpo - generated_from_trainer datasets: - Anthropic/hh-rlhf model-index: - name: llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun results: [] --- # llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-helpful-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-helpful-4xh200) on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set: - Loss: 0.6074 - Fcm Dpo/beta: 0.0011 - Fcm Dpo/q T: 0.4332 - Fcm Dpo/delta: 0.0239 - Fcm Dpo/margin: 270.7279 - Margin Dpo/margin Mean: 270.7279 - Margin Dpo/margin Std: 601.7490 - Logps/chosen: -823.2324 - Logps/rejected: -1101.7070 - Logps/ref Chosen: -79.0510 - Logps/ref Rejected: -86.7979 - Logits/chosen: -1.0197 - Logits/rejected: -1.0177 ## 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: 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 | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:------------:|:-----------:|:-------------:|:--------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 1.0801 | 0.2937 | 200 | 0.6239 | 0.0049 | 0.4392 | 0.0321 | 58.0086 | 58.0086 | 147.6546 | -225.8390 | -291.5945 | -79.0510 | -86.7979 | -0.3472 | -0.3330 | | 1.0433 | 0.5874 | 400 | 0.6033 | 0.0019 | 0.4336 | 0.0376 | 156.9007 | 156.9006 | 328.4540 | -532.2333 | -696.8809 | -79.0510 | -86.7979 | -0.5230 | -0.5119 | | 1.1393 | 0.8811 | 600 | 0.6074 | 0.0011 | 0.4332 | 0.0239 | 270.7279 | 270.7279 | 601.7490 | -823.2324 | -1101.7070 | -79.0510 | -86.7979 | -1.0197 | -1.0177 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4