metadata
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 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