zephyr-7b-dpo-qlora / README.md
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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: zephyr-7b-dpo-qlora
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-dpo-qlora
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/alignment-handbook/zephyr-7b-sft-qlora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5473
- Rewards/chosen: -0.8609
- Rewards/rejected: -1.5251
- Rewards/accuracies: 0.7422
- Rewards/margins: 0.6641
- Logps/rejected: -404.3018
- Logps/chosen: -336.2481
- Logits/rejected: 0.0706
- Logits/chosen: -0.1471
## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6812 | 0.1 | 100 | 0.6787 | 0.0452 | 0.0120 | 0.6992 | 0.0332 | -250.5929 | -245.6322 | -2.1942 | -2.2517 |
| 0.6066 | 0.21 | 200 | 0.6151 | -0.2303 | -0.5020 | 0.6992 | 0.2717 | -301.9975 | -273.1855 | -1.9906 | -2.0610 |
| 0.5711 | 0.31 | 300 | 0.5927 | -0.4441 | -0.8513 | 0.7188 | 0.4072 | -336.9228 | -294.5666 | -1.9417 | -2.0223 |
| 0.557 | 0.42 | 400 | 0.5817 | -0.5958 | -1.0732 | 0.7227 | 0.4773 | -359.1117 | -309.7378 | -1.7434 | -1.8364 |
| 0.5703 | 0.52 | 500 | 0.5679 | -0.7215 | -1.2405 | 0.7266 | 0.5189 | -375.8402 | -322.3068 | -0.8467 | -0.9967 |
| 0.5498 | 0.63 | 600 | 0.5582 | -0.7003 | -1.2848 | 0.7578 | 0.5845 | -380.2699 | -320.1794 | -0.2510 | -0.4463 |
| 0.5279 | 0.73 | 700 | 0.5490 | -0.8400 | -1.4901 | 0.75 | 0.6501 | -400.8082 | -334.1553 | 0.0145 | -0.1988 |
| 0.5264 | 0.84 | 800 | 0.5475 | -0.8613 | -1.5228 | 0.7461 | 0.6615 | -404.0751 | -336.2833 | 0.0604 | -0.1549 |
| 0.5639 | 0.94 | 900 | 0.5475 | -0.8628 | -1.5267 | 0.7422 | 0.6639 | -404.4688 | -336.4348 | 0.0704 | -0.1466 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0