--- library_name: transformers license: other base_model: flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K tags: - trl - dpo - generated_from_trainer model-index: - name: Llama-3.1-Minitron-4B-Magpie-SFT-G550K-MT-Magpo-3.1-Pro-015Mix results: [] --- # Llama-3.1-Minitron-4B-Magpie-SFT-G550K-MT-Magpo-3.1-Pro-015Mix This model is a fine-tuned version of [flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K](https://huggingface.co/flydust/Llama-3.1-Minitron-4B-Magpie-Gemma2-9B-550K) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4942 - Rewards/chosen: -3.3377 - Rewards/rejected: -4.2603 - Rewards/accuracies: 0.7620 - Rewards/margins: 0.9226 - Logps/rejected: -928.2655 - Logps/chosen: -844.1144 - Logits/rejected: -1.4591 - Logits/chosen: -1.4783 ## 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: 1.5e-07 - train_batch_size: 2 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - 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 | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6911 | 0.0653 | 100 | 0.6912 | -0.0026 | -0.0066 | 0.5640 | 0.0041 | -502.9037 | -510.6042 | -1.7834 | -1.7781 | | 0.6703 | 0.1306 | 200 | 0.6713 | -0.1429 | -0.1981 | 0.6380 | 0.0552 | -522.0521 | -524.6394 | -1.7686 | -1.7593 | | 0.6306 | 0.1959 | 300 | 0.6347 | -0.6439 | -0.8210 | 0.6840 | 0.1770 | -584.3356 | -574.7375 | -1.7536 | -1.7436 | | 0.5831 | 0.2612 | 400 | 0.5932 | -1.5155 | -1.8774 | 0.7070 | 0.3619 | -689.9788 | -661.8920 | -1.6963 | -1.6877 | | 0.5447 | 0.3266 | 500 | 0.5645 | -2.1858 | -2.7052 | 0.7110 | 0.5195 | -772.7636 | -728.9221 | -1.6249 | -1.6207 | | 0.5896 | 0.3919 | 600 | 0.5453 | -2.3771 | -2.9747 | 0.7180 | 0.5976 | -799.7122 | -748.0584 | -1.5836 | -1.5847 | | 0.5342 | 0.4572 | 700 | 0.5305 | -2.6231 | -3.3063 | 0.7350 | 0.6832 | -832.8744 | -772.6592 | -1.5454 | -1.5524 | | 0.511 | 0.5225 | 800 | 0.5177 | -3.0517 | -3.8393 | 0.7400 | 0.7876 | -886.1714 | -815.5145 | -1.5160 | -1.5273 | | 0.5007 | 0.5878 | 900 | 0.5088 | -3.0925 | -3.9197 | 0.7540 | 0.8273 | -894.2120 | -819.5908 | -1.5007 | -1.5144 | | 0.485 | 0.6531 | 1000 | 0.5033 | -3.1305 | -3.9863 | 0.7630 | 0.8558 | -900.8680 | -823.3940 | -1.4834 | -1.4997 | | 0.4307 | 0.7184 | 1100 | 0.4989 | -3.1387 | -4.0097 | 0.7610 | 0.8710 | -903.2113 | -824.2159 | -1.4728 | -1.4911 | | 0.5403 | 0.7837 | 1200 | 0.4964 | -3.3418 | -4.2574 | 0.7620 | 0.9156 | -927.9747 | -844.5242 | -1.4641 | -1.4822 | | 0.5182 | 0.8490 | 1300 | 0.4952 | -3.3255 | -4.2430 | 0.7600 | 0.9175 | -926.5396 | -842.8945 | -1.4601 | -1.4788 | | 0.5165 | 0.9144 | 1400 | 0.4943 | -3.3308 | -4.2525 | 0.7600 | 0.9217 | -927.4913 | -843.4282 | -1.4610 | -1.4799 | | 0.5192 | 0.9797 | 1500 | 0.4942 | -3.3377 | -4.2603 | 0.7620 | 0.9226 | -928.2655 | -844.1144 | -1.4591 | -1.4783 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1