--- 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 model-index: - name: zephyr-7b-uf-rlced-conifer-group-dpo-2e-alr-0.01-1e results: [] --- # zephyr-7b-uf-rlced-conifer-group-dpo-2e-alr-0.01-1e 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 dataset. It achieves the following results on the evaluation set: - Loss: 0.2572 - Rewards/chosen: -2.2030 - Rewards/rejected: -5.8511 - Rewards/accuracies: 0.8675 - Rewards/margins: 3.6481 - Logps/rejected: -988.8447 - Logps/chosen: -612.7692 - Logits/rejected: 2.2087 - Logits/chosen: 0.2455 - Excess Loss: 0.0532 - Alpha 0 Uf: 0.6287 - Alpha 1 Rlced Conifer: 0.3713 - Rewards/chosen 1 Rlced Conifer: -2.2869 - Rewards/rejected 1 Rlced Conifer: -6.6795 - Rewards/accuracies 1 Rlced Conifer: 0.9030 - Rewards/margins 1 Rlced Conifer: 4.3926 - Logps/rejected 1 Rlced Conifer: -1115.4857 - Logps/chosen 1 Rlced Conifer: -652.2682 - Logits/rejected 1 Rlced Conifer: 2.0086 - Logits/chosen 1 Rlced Conifer: -0.0625 - Task Loss 1 Rlced Conifer: 0.1962 - Task Excess Loss 1 Rlced Conifer: 0.0645 - Rewards/chosen 0 Uf: -1.8688 - Rewards/rejected 0 Uf: -2.8942 - Rewards/accuracies 0 Uf: 0.7397 - Rewards/margins 0 Uf: 1.0254 - Logps/rejected 0 Uf: -531.0295 - Logps/chosen 0 Uf: -476.1427 - Logits/rejected 0 Uf: 3.1191 - Logits/chosen 0 Uf: 1.2438 - Task Loss 0 Uf: 0.5240 - Task Excess Loss 0 Uf: 0.0664 ## 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: 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 | 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 | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:-----------:|:----------:|:---------------------:|:------------------------------:|:--------------------------------:|:----------------------------------:|:-------------------------------:|:------------------------------:|:----------------------------:|:-------------------------------:|:-----------------------------:|:-------------------------:|:--------------------------------:|:-------------------:|:---------------------:|:-----------------------:|:--------------------:|:-------------------:|:-----------------:|:--------------------:|:------------------:|:--------------:|:---------------------:| | 0.1859 | 0.2498 | 180 | 0.2923 | -1.9944 | -4.7058 | 0.8524 | 2.7115 | -874.3204 | -591.9084 | 0.9002 | -0.1249 | 0.0816 | 0.4921 | 0.5079 | -2.0854 | -5.3481 | 0.8866 | 3.2627 | -982.3445 | -632.1208 | 0.7201 | -0.3404 | 0.2278 | 0.0919 | -1.6415 | -2.4124 | 0.7158 | 0.7709 | -482.8499 | -453.4123 | 1.6757 | 0.5476 | 0.5480 | 0.1058 | | 0.1646 | 0.4997 | 360 | 0.2654 | -2.3703 | -5.8263 | 0.8637 | 3.4560 | -986.3652 | -629.4960 | 1.5662 | -0.2281 | 0.0630 | 0.5888 | 0.4112 | -2.4491 | -6.6305 | 0.8988 | 4.1814 | -1110.5859 | -668.4894 | 1.4570 | -0.4928 | 0.2047 | 0.0719 | -2.0521 | -2.9610 | 0.7379 | 0.9089 | -537.7054 | -494.4703 | 2.1435 | 0.6282 | 0.5444 | 0.0878 | | 0.162 | 0.7495 | 540 | 0.2603 | -2.0719 | -5.7198 | 0.8637 | 3.6479 | -975.7140 | -599.6583 | 1.8052 | -0.3472 | 0.0563 | 0.6201 | 0.3799 | -2.1783 | -6.5775 | 0.9020 | 4.3992 | -1105.2861 | -641.4061 | 1.6728 | -0.6324 | 0.1991 | 0.0667 | -1.6637 | -2.6673 | 0.7294 | 1.0036 | -508.3393 | -455.6315 | 2.4641 | 0.5657 | 0.5322 | 0.0717 | | 0.1476 | 0.9993 | 720 | 0.2572 | -2.2030 | -5.8511 | 0.8675 | 3.6481 | -988.8447 | -612.7692 | 2.2087 | 0.2455 | 0.0532 | 0.6287 | 0.3713 | -2.2869 | -6.6795 | 0.9030 | 4.3926 | -1115.4857 | -652.2682 | 2.0086 | -0.0625 | 0.1962 | 0.0645 | -1.8688 | -2.8942 | 0.7397 | 1.0254 | -531.0295 | -476.1427 | 3.1191 | 1.2438 | 0.5240 | 0.0664 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.0a0+81ea7a4 - Datasets 2.21.0 - Tokenizers 0.19.1