---
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-gpt-reward-scale-01
  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-reward-scale-01

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: 0.5383
- Rewards/chosen: -1.3950
- Rewards/rejected: -2.4464
- Rewards/accuracies: 0.7241
- Rewards/margins: 1.0514
- Logps/rejected: -490.2826
- Logps/chosen: -423.5039
- Logits/rejected: 1.2749
- Logits/chosen: -0.2527

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.674         | 0.1147 | 50   | 0.6644          | -0.0456        | -0.1442          | 0.6724             | 0.0986          | -260.0650      | -288.5642    | -2.5039         | -2.6023       |
| 0.5874        | 0.2294 | 100  | 0.5920          | -0.9820        | -1.5650          | 0.6810             | 0.5830          | -402.1482      | -382.2076    | 0.3008          | -0.2226       |
| 0.5612        | 0.3440 | 150  | 0.5695          | -1.4677        | -2.3665          | 0.6897             | 0.8989          | -482.2998      | -430.7732    | 2.3140          | 1.4310        |
| 0.5427        | 0.4587 | 200  | 0.5523          | -1.3469        | -2.2624          | 0.7241             | 0.9156          | -471.8922      | -418.6947    | 0.9223          | -0.3630       |
| 0.5474        | 0.5734 | 250  | 0.5430          | -1.0958        | -2.0370          | 0.6897             | 0.9412          | -449.3501      | -393.5861    | 0.9071          | -0.4403       |
| 0.5556        | 0.6881 | 300  | 0.5404          | -1.3959        | -2.3862          | 0.7198             | 0.9903          | -484.2666      | -423.5919    | 1.1950          | -0.1993       |
| 0.5373        | 0.8028 | 350  | 0.5416          | -1.5583        | -2.5998          | 0.7284             | 1.0414          | -505.6230      | -439.8387    | 1.7159          | 0.2396        |
| 0.5405        | 0.9174 | 400  | 0.5383          | -1.3950        | -2.4464          | 0.7241             | 1.0514          | -490.2826      | -423.5039    | 1.2749          | -0.2527       |


### Framework versions

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