---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b
  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

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: 0.6918
- Rewards/chosen: -0.0862
- Rewards/rejected: -0.1980
- Rewards/accuracies: 0.3591
- Rewards/margins: 0.1117
- Logps/rejected: -95.1937
- Logps/chosen: -77.5232
- Logits/rejected: -1.9123
- Logits/chosen: -1.9402
- Use Label: 15333.4131
- Pred Label: 4738.5874

## 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 | Use Label  | Pred Label |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------:|:----------:|
| 0.6876        | 0.1   | 100  | 0.6896          | -0.0555        | -0.0989          | 0.3353             | 0.0434          | -85.2883       | -74.4495     | -2.0761         | -2.1076       | 1766.8572  | 89.1429    |
| 0.6892        | 0.21  | 200  | 0.6894          | -0.0049        | -0.0560          | 0.3492             | 0.0511          | -80.9954       | -69.3876     | -2.0287         | -2.0520       | 3500.8889  | 459.1111   |
| 0.6904        | 0.31  | 300  | 0.6909          | -0.0625        | -0.1410          | 0.3532             | 0.0785          | -89.5016       | -75.1524     | -1.9943         | -2.0164       | 5140.6826  | 923.3174   |
| 0.6906        | 0.42  | 400  | 0.6921          | -0.0637        | -0.1541          | 0.3512             | 0.0904          | -90.8064       | -75.2687     | -2.0248         | -2.0481       | 6695.4287  | 1472.5714  |
| 0.6903        | 0.52  | 500  | 0.6914          | -0.0747        | -0.1726          | 0.3492             | 0.0979          | -92.6561       | -76.3697     | -1.9801         | -2.0071       | 8246.2061  | 2025.7937  |
| 0.6903        | 0.63  | 600  | 0.6917          | -0.1005        | -0.2047          | 0.3552             | 0.1042          | -95.8670       | -78.9543     | -1.9601         | -1.9870       | 9772.0635  | 2603.9365  |
| 0.6917        | 0.73  | 700  | 0.6917          | -0.1117        | -0.2224          | 0.3512             | 0.1108          | -97.6411       | -80.0681     | -1.9401         | -1.9659       | 11284.7773 | 3195.2222  |
| 0.6912        | 0.84  | 800  | 0.6917          | -0.0869        | -0.1981          | 0.3631             | 0.1112          | -95.2089       | -77.5874     | -1.9144         | -1.9422       | 12826.8252 | 3757.1746  |
| 0.6914        | 0.94  | 900  | 0.6918          | -0.0863        | -0.1983          | 0.3571             | 0.1120          | -95.2291       | -77.5275     | -1.9113         | -1.9391       | 14335.7139 | 4352.2856  |


### Framework versions

- PEFT 0.7.1
- Transformers 4.38.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2