---
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-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: 0.0341
- Rewards/chosen: -0.0738
- Rewards/rejected: -0.3717
- Rewards/accuracies: 0.7414
- Rewards/margins: 0.2979
- Logps/rejected: -256.2462
- Logps/chosen: -282.9861
- Logits/rejected: -2.4523
- Logits/chosen: -2.5611

## 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          | 0.0621         | -0.0550          | 0.7026             | 0.1170          | -224.5715      | -269.3974    | -2.4545         | -2.5523       |
| 0.04          | 0.2286 | 100  | 0.0385          | -0.0777        | -0.3186          | 0.75               | 0.2409          | -250.9367      | -283.3715    | -1.9565         | -2.1306       |
| 0.0363        | 0.3429 | 150  | 0.0371          | -0.2052        | -0.4595          | 0.7543             | 0.2543          | -265.0228      | -296.1211    | -2.1955         | -2.3441       |
| 0.0373        | 0.4571 | 200  | 0.0353          | -0.0452        | -0.3269          | 0.7716             | 0.2817          | -251.7630      | -280.1239    | -2.3848         | -2.4903       |
| 0.0374        | 0.5714 | 250  | 0.0344          | -0.0802        | -0.3463          | 0.75               | 0.2662          | -253.7082      | -283.6198    | -2.4307         | -2.5245       |
| 0.0346        | 0.6857 | 300  | 0.0342          | -0.0372        | -0.3195          | 0.7457             | 0.2823          | -251.0285      | -279.3270    | -2.4797         | -2.5812       |
| 0.0375        | 0.8    | 350  | 0.0342          | -0.0783        | -0.3746          | 0.7414             | 0.2963          | -256.5389      | -283.4324    | -2.4474         | -2.5561       |
| 0.0367        | 0.9143 | 400  | 0.0341          | -0.0738        | -0.3717          | 0.7414             | 0.2979          | -256.2462      | -282.9861    | -2.4523         | -2.5611       |


### Framework versions

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