--- library_name: transformers base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200 tags: - alignment-handbook - new-dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.4 results: [] --- # llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.4 This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.5983 - Fcm Dpo/beta: 0.0027 - Margin Dpo/margin Mean: 105.4011 - Margin Dpo/margin Std: 182.7466 - Logps/chosen: -546.8945 - Logps/rejected: -631.3989 - Logps/ref Chosen: -287.8268 - Logps/ref Rejected: -266.9300 - Kl/chosen Kl Mean: -259.0677 - Kl/rejected Kl Mean: -364.4689 - Kl/mean: -311.7683 - Kl/std: 162.3682 - Logits/chosen: -0.8539 - Logits/rejected: -0.8364 ## 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: 4 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - total_eval_batch_size: 8 - 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 | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Kl/chosen Kl Mean | Kl/rejected Kl Mean | Kl/mean | Kl/std | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-----------------:|:-------------------:|:---------:|:--------:|:-------------:|:---------------:| | 4.9173 | 0.4188 | 200 | 0.5938 | 0.0054 | 55.2587 | 96.2979 | -406.3043 | -440.6663 | -287.8268 | -266.9300 | -118.4775 | -173.7362 | -146.1068 | 87.6889 | -0.9034 | -0.8850 | | 4.8145 | 0.8377 | 400 | 0.5983 | 0.0027 | 105.4011 | 182.7466 | -546.8945 | -631.3989 | -287.8268 | -266.9300 | -259.0677 | -364.4689 | -311.7683 | 162.3682 | -0.8539 | -0.8364 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4