---
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full
  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-full

This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4965
- Rewards/chosen: -2.9708
- Rewards/rejected: -4.3017
- Rewards/accuracies: 0.7695
- Rewards/margins: 1.3309
- Logps/rejected: -687.5271
- Logps/chosen: -554.1226
- Logits/rejected: -0.1928
- Logits/chosen: -0.6531

## 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: 8
- eval_batch_size: 8
- seed: 3
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5326        | 0.11  | 100  | 0.6180          | -0.4024        | -0.6993          | 0.6797             | 0.2969          | -327.2873      | -297.2842    | -2.5800         | -2.5958       |
| 0.4709        | 0.23  | 200  | 0.5608          | -1.1383        | -1.7616          | 0.7109             | 0.6233          | -433.5121      | -370.8716    | -2.1515         | -2.1720       |
| 0.4289        | 0.34  | 300  | 0.5293          | -1.5404        | -2.3958          | 0.7539             | 0.8554          | -496.9380      | -411.0811    | -2.0882         | -2.1204       |
| 0.4195        | 0.45  | 400  | 0.5096          | -1.7916        | -2.8995          | 0.7812             | 1.1079          | -547.3041      | -436.1970    | -1.0571         | -1.2976       |
| 0.3891        | 0.57  | 500  | 0.5086          | -2.6047        | -3.9255          | 0.7812             | 1.3208          | -649.9016      | -517.5072    | -0.8608         | -1.1314       |
| 0.4182        | 0.68  | 600  | 0.4976          | -2.4968        | -3.7962          | 0.7695             | 1.2994          | -636.9742      | -506.7195    | -0.4354         | -0.8384       |
| 0.3845        | 0.79  | 700  | 0.4967          | -2.6976        | -4.0084          | 0.7695             | 1.3108          | -658.1885      | -526.7999    | -0.2826         | -0.7200       |
| 0.3896        | 0.91  | 800  | 0.4965          | -2.9708        | -4.3017          | 0.7695             | 1.3309          | -687.5271      | -554.1226    | -0.1928         | -0.6531       |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1