---
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
  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

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: 0.5209
- Rewards/chosen: -1.1123
- Rewards/rejected: -2.3595
- Rewards/accuracies: 0.7672
- Rewards/margins: 1.2472
- Logps/rejected: -455.0307
- Logps/chosen: -386.8380
- Logits/rejected: 3.7050
- Logits/chosen: 2.1175

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6663        | 0.1143 | 50   | 0.6532          | -0.0060        | -0.1654          | 0.6897             | 0.1594          | -235.6116      | -276.2017    | -2.4378         | -2.5412       |
| 0.6051        | 0.2286 | 100  | 0.6128          | -0.8115        | -1.2713          | 0.7112             | 0.4599          | -346.2107      | -356.7497    | -2.3746         | -2.4933       |
| 0.5375        | 0.3429 | 150  | 0.5487          | -0.8314        | -1.9411          | 0.7672             | 1.1097          | -413.1859      | -358.7466    | 1.3727          | 0.2031        |
| 0.5435        | 0.4571 | 200  | 0.5359          | -0.9895        | -2.0771          | 0.7543             | 1.0876          | -426.7858      | -374.5490    | 2.7076          | 1.3441        |
| 0.5433        | 0.5714 | 250  | 0.5290          | -0.9003        | -2.0663          | 0.7629             | 1.1660          | -425.7063      | -365.6371    | 2.4121          | 0.8588        |
| 0.5194        | 0.6857 | 300  | 0.5213          | -0.9607        | -2.2057          | 0.7716             | 1.2450          | -439.6500      | -371.6745    | 3.3117          | 1.7085        |
| 0.5325        | 0.8    | 350  | 0.5216          | -1.1386        | -2.3763          | 0.7629             | 1.2377          | -456.7085      | -389.4649    | 3.6708          | 2.0842        |
| 0.5483        | 0.9143 | 400  | 0.5209          | -1.1123        | -2.3595          | 0.7672             | 1.2472          | -455.0307      | -386.8380    | 3.7050          | 2.1175        |


### Framework versions

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