---
base_model: HuggingFaceH4/mistral-7b-ift
tags:
- generated_from_trainer
model-index:
- name: mistral-7b-dpo-v0.4
  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. -->

# mistral-7b-dpo-v0.4

This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-ift](https://huggingface.co/HuggingFaceH4/mistral-7b-ift) on the HuggingFaceH4/ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4605
- Rewards/chosen: -0.5053
- Rewards/rejected: -1.8752
- Rewards/accuracies: 0.7812
- Rewards/margins: 1.3699
- Logps/rejected: -327.4286
- Logps/chosen: -297.1040
- Logits/rejected: -2.7153
- Logits/chosen: -2.7447

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5602        | 0.05  | 100  | 0.5589          | -0.3359        | -0.8168          | 0.7188             | 0.4809          | -306.2607      | -293.7161    | -2.6554         | -2.6797       |
| 0.4852        | 0.1   | 200  | 0.5136          | -0.5310        | -1.4994          | 0.8125             | 0.9684          | -319.9124      | -297.6181    | -2.5762         | -2.5957       |
| 0.5212        | 0.15  | 300  | 0.5168          | -0.1686        | -1.1760          | 0.7812             | 1.0074          | -313.4444      | -290.3699    | -2.6865         | -2.7125       |
| 0.5496        | 0.21  | 400  | 0.4835          | -0.1617        | -1.7170          | 0.8281             | 1.5552          | -324.2635      | -290.2326    | -2.7947         | -2.8218       |
| 0.5209        | 0.26  | 500  | 0.5054          | -0.4778        | -1.6604          | 0.7344             | 1.1826          | -323.1325      | -296.5546    | -2.8388         | -2.8667       |
| 0.4617        | 0.31  | 600  | 0.4910          | -0.3738        | -1.5180          | 0.7656             | 1.1442          | -320.2848      | -294.4741    | -2.8234         | -2.8521       |
| 0.4452        | 0.36  | 700  | 0.4838          | -0.4591        | -1.6576          | 0.7031             | 1.1986          | -323.0770      | -296.1796    | -2.7401         | -2.7653       |
| 0.4674        | 0.41  | 800  | 0.5077          | -0.5692        | -1.8659          | 0.7656             | 1.2967          | -327.2416      | -298.3818    | -2.6740         | -2.6945       |
| 0.4656        | 0.46  | 900  | 0.4927          | -0.5279        | -1.6614          | 0.7656             | 1.1335          | -323.1518      | -297.5553    | -2.7817         | -2.8015       |
| 0.4102        | 0.52  | 1000 | 0.4772          | -0.5767        | -2.0667          | 0.7656             | 1.4900          | -331.2578      | -298.5311    | -2.7160         | -2.7455       |
| 0.4663        | 0.57  | 1100 | 0.4740          | -0.8038        | -2.1018          | 0.7656             | 1.2980          | -331.9604      | -303.0741    | -2.6994         | -2.7257       |
| 0.4737        | 0.62  | 1200 | 0.4716          | -0.3783        | -1.7015          | 0.7969             | 1.3232          | -323.9545      | -294.5634    | -2.6842         | -2.7135       |
| 0.4259        | 0.67  | 1300 | 0.4866          | -0.6239        | -1.9703          | 0.7812             | 1.3464          | -329.3312      | -299.4761    | -2.7046         | -2.7356       |
| 0.4935        | 0.72  | 1400 | 0.4747          | -0.5626        | -1.7600          | 0.7812             | 1.1974          | -325.1243      | -298.2491    | -2.7153         | -2.7444       |
| 0.4211        | 0.77  | 1500 | 0.4645          | -0.6099        | -1.9993          | 0.7656             | 1.3894          | -329.9109      | -299.1959    | -2.6944         | -2.7236       |
| 0.4931        | 0.83  | 1600 | 0.4684          | -0.6798        | -2.1082          | 0.7656             | 1.4285          | -332.0890      | -300.5934    | -2.7006         | -2.7305       |
| 0.5029        | 0.88  | 1700 | 0.4595          | -0.5063        | -1.8951          | 0.7812             | 1.3889          | -327.8267      | -297.1233    | -2.7108         | -2.7403       |
| 0.4965        | 0.93  | 1800 | 0.4613          | -0.5561        | -1.9079          | 0.7812             | 1.3518          | -328.0831      | -298.1203    | -2.7226         | -2.7523       |
| 0.4337        | 0.98  | 1900 | 0.4608          | -0.5066        | -1.8718          | 0.7656             | 1.3652          | -327.3599      | -297.1296    | -2.7175         | -2.7469       |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.14.0