---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-gpt_consistent-reward-scale-1-rpo
  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-gpt_consistent-reward-scale-1-rpo

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0087
- Rewards/chosen: -0.0010
- Rewards/rejected: -0.1538
- Rewards/accuracies: 0.7759
- Rewards/margins: 0.1527
- Logps/rejected: -261.8980
- Logps/chosen: -285.1917
- Logits/rejected: -2.3893
- Logits/chosen: -2.4834

## 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: 55
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.012         | 0.1147 | 50   | 0.0113          | 0.0776         | -0.0073          | 0.6983             | 0.0849          | -247.2525      | -277.3343    | -2.5025         | -2.5786       |
| 0.0111        | 0.2294 | 100  | 0.0100          | 0.0400         | -0.0817          | 0.7112             | 0.1217          | -254.6882      | -281.0889    | -2.3452         | -2.4456       |
| 0.0104        | 0.3440 | 150  | 0.0098          | -0.0092        | -0.1421          | 0.7284             | 0.1329          | -260.7338      | -286.0115    | -2.4006         | -2.4971       |
| 0.0096        | 0.4587 | 200  | 0.0093          | 0.0230         | -0.1186          | 0.7888             | 0.1416          | -258.3851      | -282.7939    | -2.4206         | -2.5115       |
| 0.0093        | 0.5734 | 250  | 0.0089          | -0.0116        | -0.1682          | 0.7845             | 0.1565          | -263.3386      | -286.2548    | -2.3653         | -2.4591       |
| 0.0096        | 0.6881 | 300  | 0.0088          | -0.0083        | -0.1589          | 0.7845             | 0.1506          | -262.4115      | -285.9173    | -2.3891         | -2.4814       |
| 0.0096        | 0.8028 | 350  | 0.0087          | -0.0041        | -0.1596          | 0.7802             | 0.1555          | -262.4817      | -285.5014    | -2.3906         | -2.4846       |
| 0.0093        | 0.9174 | 400  | 0.0087          | -0.0010        | -0.1538          | 0.7759             | 0.1527          | -261.8980      | -285.1917    | -2.3893         | -2.4834       |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1