--- library_name: transformers license: apache-2.0 base_model: Qwen/Qwen2.5-32B-Instruct tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - tanliboy/orca_dpo_pairs model-index: - name: lambda-qwen2.5-32b-dpo-test results: [] --- # lambda-qwen2.5-32b-dpo-test This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co./Qwen/Qwen2.5-32B-Instruct) on the tanliboy/orca_dpo_pairs dataset. It achieves the following results on the evaluation set: - Loss: 0.0003 - Rewards/chosen: -10.1618 - Rewards/rejected: -26.1150 - Rewards/accuracies: 1.0 - Rewards/margins: 15.9532 - Logps/rejected: -3049.5271 - Logps/chosen: -1372.8903 - Logits/rejected: -0.3154 - Logits/chosen: -0.0600 ## 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: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 16 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.0103 | 0.2618 | 100 | 0.0060 | -8.5159 | -18.7731 | 1.0 | 10.2572 | -2315.3333 | -1208.2968 | -0.5485 | -0.2481 | | 0.0005 | 0.5236 | 200 | 0.0005 | -9.9255 | -24.9117 | 1.0 | 14.9862 | -2929.1948 | -1349.2588 | -0.3723 | -0.0661 | | 0.0005 | 0.7853 | 300 | 0.0004 | -10.0873 | -25.9319 | 1.0 | 15.8446 | -3031.2175 | -1365.4342 | -0.2882 | -0.0014 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1