---
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: 0.1422
- Rewards/chosen: -1.3154
- Rewards/rejected: -2.2768
- Rewards/accuracies: 0.7617
- Rewards/margins: 0.9613
- Logps/rejected: -483.9327
- Logps/chosen: -386.7366
- Logits/rejected: -2.1695
- Logits/chosen: -2.2036
- Debug/policy Weights: 0.2815
- Debug/losses: 0.1397
- Debug/raw Losses: 0.4727

## 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: 42
- 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 | Debug/policy Weights | Debug/losses | Debug/raw Losses |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------------------:|:------------:|:----------------:|
| 0.1781        | 0.21  | 100  | 0.2007          | -0.6478        | -1.1693          | 0.7344             | 0.5214          | -373.1867      | -319.9806    | -2.6910         | -2.7080       | 0.3512               | 0.1953       | 0.5590           |
| 0.1616        | 0.42  | 200  | 0.1669          | -0.8830        | -1.6003          | 0.7109             | 0.7173          | -416.2844      | -343.4914    | -2.4277         | -2.4499       | 0.3174               | 0.1671       | 0.5079           |
| 0.1343        | 0.63  | 300  | 0.1368          | -1.5021        | -2.3715          | 0.7578             | 0.8695          | -493.4114      | -405.4042    | -2.2283         | -2.2618       | 0.2666               | 0.1365       | 0.4953           |
| 0.1398        | 0.84  | 400  | 0.1422          | -1.3154        | -2.2768          | 0.7617             | 0.9613          | -483.9327      | -386.7366    | -2.1695         | -2.2036       | 0.2815               | 0.1397       | 0.4727           |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2