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---
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
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
should probably proofread and complete it, then remove this comment. -->
# 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: 0.4945
- Rewards/chosen: -2.5530
- Rewards/rejected: -3.6159
- Rewards/accuracies: 0.7778
- Rewards/margins: 1.0629
- Logps/rejected: -606.2373
- Logps/chosen: -520.2218
- Logits/rejected: -0.9908
- Logits/chosen: -1.1030
## 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: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6212 | 0.1047 | 100 | 0.6321 | -0.3313 | -0.5450 | 0.6944 | 0.2137 | -299.1472 | -298.0506 | -2.0086 | -2.0933 |
| 0.5618 | 0.2094 | 200 | 0.5601 | -0.8198 | -1.3660 | 0.7222 | 0.5461 | -381.2446 | -346.9064 | -1.6694 | -1.7551 |
| 0.54 | 0.3141 | 300 | 0.5265 | -1.5221 | -2.3343 | 0.7460 | 0.8122 | -478.0748 | -417.1275 | -1.0704 | -1.1715 |
| 0.5261 | 0.4187 | 400 | 0.5082 | -1.6553 | -2.5263 | 0.7540 | 0.8710 | -497.2759 | -430.4526 | -1.1014 | -1.2013 |
| 0.5107 | 0.5234 | 500 | 0.5059 | -2.4506 | -3.4250 | 0.75 | 0.9744 | -587.1476 | -509.9848 | -0.9852 | -1.0956 |
| 0.4851 | 0.6281 | 600 | 0.5023 | -2.2726 | -3.2316 | 0.7679 | 0.9590 | -567.8049 | -492.1783 | -0.9970 | -1.1078 |
| 0.4681 | 0.7328 | 700 | 0.4993 | -2.3170 | -3.3688 | 0.7679 | 1.0517 | -581.5197 | -496.6232 | -1.0068 | -1.1190 |
| 0.4852 | 0.8375 | 800 | 0.4950 | -2.3970 | -3.4117 | 0.7738 | 1.0147 | -585.8156 | -504.6183 | -1.0237 | -1.1353 |
| 0.4907 | 0.9422 | 900 | 0.4945 | -2.5678 | -3.6349 | 0.7778 | 1.0671 | -608.1346 | -521.7063 | -0.9901 | -1.1024 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1 |