|
--- |
|
license: apache-2.0 |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- dpo |
|
- generated_from_trainer |
|
base_model: alignment-handbook/zephyr-7b-sft-full |
|
datasets: |
|
- generation/GPT4 |
|
model-index: |
|
- name: zephyr-dpo-qlora-gpt4-5e-6-epoch3 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# zephyr-dpo-qlora-gpt4-5e-6-epoch3 |
|
|
|
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 generation/GPT4 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8389 |
|
- Rewards/chosen: -16.6323 |
|
- Rewards/rejected: -19.5704 |
|
- Rewards/accuracies: 0.6905 |
|
- Rewards/margins: 2.9381 |
|
- Rewards/margins Max: 11.9980 |
|
- Rewards/margins Min: -5.2949 |
|
- Rewards/margins Std: 7.7821 |
|
- Logps/rejected: -2216.2207 |
|
- Logps/chosen: -1948.4508 |
|
- Logits/rejected: -1.4331 |
|
- Logits/chosen: -1.5188 |
|
|
|
## 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-06 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- total_train_batch_size: 16 |
|
- total_eval_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Rewards/margins Max | Rewards/margins Min | Rewards/margins Std | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.4777 | 0.28 | 100 | 0.6755 | -0.3600 | -0.4244 | 0.6032 | 0.0644 | 0.3559 | -0.2210 | 0.2529 | -301.6254 | -321.2222 | -2.6312 | -2.6710 | |
|
| 0.1416 | 0.56 | 200 | 0.9053 | -6.7040 | -7.2161 | 0.6270 | 0.5121 | 2.7698 | -1.7984 | 2.0239 | -980.7882 | -955.6170 | -1.4055 | -1.4608 | |
|
| 0.0426 | 0.85 | 300 | 0.9213 | -7.5636 | -8.6200 | 0.6786 | 1.0563 | 4.2652 | -2.1614 | 2.8565 | -1121.1776 | -1041.5824 | -1.6508 | -1.7101 | |
|
| 0.0537 | 1.13 | 400 | 1.1419 | -12.1996 | -13.1820 | 0.6468 | 0.9824 | 5.4879 | -3.0621 | 3.7889 | -1577.3877 | -1505.1829 | -1.5926 | -1.6576 | |
|
| 0.0197 | 1.41 | 500 | 1.6844 | -17.1495 | -18.8730 | 0.6667 | 1.7235 | 9.4195 | -5.1462 | 6.5774 | -2146.4797 | -2000.1663 | -1.4330 | -1.5026 | |
|
| 0.0029 | 1.69 | 600 | 1.9743 | -14.5461 | -17.4661 | 0.6865 | 2.9200 | 12.4008 | -5.7167 | 8.1643 | -2005.7900 | -1739.8331 | -1.4547 | -1.5331 | |
|
| 0.018 | 1.97 | 700 | 1.8030 | -16.5306 | -19.1782 | 0.6786 | 2.6476 | 11.2308 | -5.2715 | 7.4338 | -2177.0017 | -1938.2783 | -1.4133 | -1.4978 | |
|
| 0.0014 | 2.25 | 800 | 1.8519 | -16.7236 | -19.4930 | 0.6746 | 2.7694 | 11.6630 | -5.3047 | 7.6237 | -2208.4844 | -1957.5789 | -1.4433 | -1.5266 | |
|
| 0.0034 | 2.54 | 900 | 1.6799 | -16.1476 | -18.7797 | 0.6865 | 2.6322 | 10.7631 | -4.8758 | 7.0339 | -2137.1570 | -1899.9781 | -1.4489 | -1.5324 | |
|
| 0.0118 | 2.82 | 1000 | 1.8351 | -16.6710 | -19.6029 | 0.6825 | 2.9319 | 11.9629 | -5.2899 | 7.7662 | -2219.4746 | -1952.3245 | -1.4296 | -1.5156 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.7.1 |
|
- Transformers 4.39.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.15.2 |
