---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-prometheus_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-prometheus_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: 0.0340
- Rewards/chosen: -0.0965
- Rewards/rejected: -0.3938
- Rewards/accuracies: 0.7414
- Rewards/margins: 0.2973
- Logps/rejected: -258.4546
- Logps/chosen: -285.2520
- Logits/rejected: -2.1563
- Logits/chosen: -2.3140

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.048         | 0.1143 | 50   | 0.0428          | 0.0615         | -0.0563          | 0.7026             | 0.1178          | -224.7078      | -269.4535    | -2.4545         | -2.5520       |
| 0.0399        | 0.2286 | 100  | 0.0385          | -0.0747        | -0.3118          | 0.75               | 0.2371          | -250.2514      | -283.0706    | -1.9893         | -2.1601       |
| 0.0367        | 0.3429 | 150  | 0.0371          | -0.1934        | -0.4431          | 0.7672             | 0.2497          | -263.3893      | -294.9446    | -2.3057         | -2.4218       |
| 0.0375        | 0.4571 | 200  | 0.0353          | -0.0541        | -0.3320          | 0.7672             | 0.2779          | -252.2786      | -281.0130    | -2.1436         | -2.2907       |
| 0.0371        | 0.5714 | 250  | 0.0344          | -0.0812        | -0.3496          | 0.7629             | 0.2684          | -254.0325      | -283.7219    | -2.2615         | -2.3785       |
| 0.0345        | 0.6857 | 300  | 0.0341          | -0.0682        | -0.3495          | 0.7457             | 0.2813          | -254.0265      | -282.4234    | -2.2130         | -2.3475       |
| 0.0373        | 0.8    | 350  | 0.0341          | -0.0908        | -0.3849          | 0.7414             | 0.2941          | -257.5619      | -284.6819    | -2.1788         | -2.3321       |
| 0.0367        | 0.9143 | 400  | 0.0340          | -0.0965        | -0.3938          | 0.7414             | 0.2973          | -258.4546      | -285.2520    | -2.1563         | -2.3140       |


### Framework versions

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