--- library_name: transformers license: apache-2.0 base_model: alignment-handbook/zephyr-7b-sft-full tags: - alignment-handbook - trl - dpo - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - data/zephyr_uf_rlced_conifer_ref_1e2e model-index: - name: zephyr-7b-uf-rlced-conifer-1e2e-group-dpo-2e results: [] --- # zephyr-7b-uf-rlced-conifer-1e2e-group-dpo-2e This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the data/zephyr_uf_rlced_conifer_ref_1e2e dataset. It achieves the following results on the evaluation set: - Loss: 0.2626 - Rewards/chosen: -2.1843 - Rewards/rejected: -5.4288 - Rewards/accuracies: 0.8684 - Rewards/margins: 3.2445 - Logps/rejected: -946.6157 - Logps/chosen: -610.9032 - Logits/rejected: 1.2318 - Logits/chosen: -0.7806 - Excess Loss: 0.0374 - Alpha 0 Uf: 0.8470 - Alpha 1 Rlced Conifer: 0.1530 - Rewards/chosen 1 Rlced Conifer: -2.2281 - Rewards/rejected 1 Rlced Conifer: -6.0246 - Rewards/accuracies 1 Rlced Conifer: 0.8987 - Rewards/margins 1 Rlced Conifer: 3.7965 - Logps/rejected 1 Rlced Conifer: -1049.9939 - Logps/chosen 1 Rlced Conifer: -646.3860 - Logits/rejected 1 Rlced Conifer: 1.1158 - Logits/chosen 1 Rlced Conifer: -0.9982 - Task Loss 1 Rlced Conifer: 0.2102 - Task Excess Loss 1 Rlced Conifer: 0.0475 - Rewards/chosen 0 Uf: -1.9978 - Rewards/rejected 0 Uf: -3.3091 - Rewards/accuracies 0 Uf: 0.7603 - Rewards/margins 0 Uf: 1.3113 - Logps/rejected 0 Uf: -572.5212 - Logps/chosen 0 Uf: -489.0419 - Logits/rejected 0 Uf: 1.8243 - Logits/chosen 0 Uf: -0.1004 - Task Loss 0 Uf: 0.4944 - Task Excess Loss 0 Uf: 0.0469 ## 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: 8 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - total_eval_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Excess Loss | Alpha 0 Uf | Alpha 1 Rlced Conifer | Rewards/chosen 1 Rlced Conifer | Rewards/rejected 1 Rlced Conifer | Rewards/accuracies 1 Rlced Conifer | Rewards/margins 1 Rlced Conifer | Logps/rejected 1 Rlced Conifer | Logps/chosen 1 Rlced Conifer | Logits/rejected 1 Rlced Conifer | Logits/chosen 1 Rlced Conifer | Task Loss 1 Rlced Conifer | Task Excess Loss 1 Rlced Conifer | Rewards/chosen 0 Uf | Rewards/rejected 0 Uf | Rewards/accuracies 0 Uf | Rewards/margins 0 Uf | Logps/rejected 0 Uf | Logps/chosen 0 Uf | Logits/rejected 0 Uf | Logits/chosen 0 Uf | Task Loss 0 Uf | Task Excess Loss 0 Uf | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:-----------:|:----------:|:---------------------:|:------------------------------:|:--------------------------------:|:----------------------------------:|:-------------------------------:|:------------------------------:|:----------------------------:|:-------------------------------:|:-----------------------------:|:-------------------------:|:--------------------------------:|:-------------------:|:---------------------:|:-----------------------:|:--------------------:|:-------------------:|:-----------------:|:--------------------:|:------------------:|:--------------:|:---------------------:| | 0.1953 | 0.4997 | 360 | 0.3535 | -1.5938 | -3.1996 | 0.8402 | 1.6058 | -723.6984 | -551.8521 | 0.1112 | -0.7863 | 0.1136 | 0.9694 | 0.0306 | -1.5989 | -3.4179 | 0.8677 | 1.8190 | -789.3262 | -583.4747 | -0.1145 | -0.9516 | 0.3087 | 0.1414 | -1.5520 | -2.3972 | 0.7448 | 0.8452 | -481.3242 | -444.4588 | 1.0137 | -0.2527 | 0.5289 | 0.0768 | | 0.1537 | 0.9993 | 720 | 0.3329 | -1.4289 | -3.2979 | 0.8609 | 1.8690 | -733.5210 | -535.3586 | 0.6830 | -0.5276 | 0.0943 | 0.9852 | 0.0148 | -1.4038 | -3.4887 | 0.8869 | 2.0849 | -796.4048 | -563.9600 | 0.3914 | -0.7372 | 0.2955 | 0.1278 | -1.4972 | -2.5982 | 0.7618 | 1.1009 | -501.4233 | -438.9818 | 1.8477 | 0.1514 | 0.4804 | 0.0530 | | 0.0667 | 1.4990 | 1080 | 0.2667 | -2.1402 | -5.1839 | 0.8656 | 3.0437 | -922.1221 | -606.4852 | 1.0002 | -0.7884 | 0.0408 | 0.8954 | 0.1046 | -2.1729 | -5.7323 | 0.8964 | 3.5594 | -1020.7665 | -640.8754 | 0.8903 | -0.9784 | 0.2150 | 0.0521 | -1.9916 | -3.2293 | 0.7574 | 1.2377 | -564.5363 | -488.4239 | 1.5582 | -0.1961 | 0.4940 | 0.0466 | | 0.06 | 1.9986 | 1440 | 0.2626 | -2.1843 | -5.4288 | 0.8684 | 3.2445 | -946.6157 | -610.9032 | 1.2318 | -0.7806 | 0.0374 | 0.8470 | 0.1530 | -2.2281 | -6.0246 | 0.8987 | 3.7965 | -1049.9939 | -646.3860 | 1.1158 | -0.9982 | 0.2102 | 0.0475 | -1.9978 | -3.3091 | 0.7603 | 1.3113 | -572.5212 | -489.0419 | 1.8243 | -0.1004 | 0.4944 | 0.0469 | ### Framework versions - Transformers 4.44.1 - Pytorch 2.1.2+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1