---
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_consistent-reward-scale-05
  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-05

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: 0.4931
- Rewards/chosen: -1.6483
- Rewards/rejected: -2.9482
- Rewards/accuracies: 0.7414
- Rewards/margins: 1.2999
- Logps/rejected: -541.3424
- Logps/chosen: -449.9160
- Logits/rejected: 3.3584
- Logits/chosen: 2.0773

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6653        | 0.1147 | 50   | 0.6513          | -0.0038        | -0.1422          | 0.6940             | 0.1384          | -260.7392      | -285.4682    | -2.4923         | -2.5731       |
| 0.5699        | 0.2294 | 100  | 0.5578          | -0.8876        | -1.6121          | 0.6853             | 0.7245          | -407.7342      | -373.8545    | 0.8771          | 0.3393        |
| 0.5416        | 0.3440 | 150  | 0.5320          | -1.1447        | -2.1157          | 0.7026             | 0.9709          | -458.0881      | -399.5647    | 2.1978          | 1.2442        |
| 0.5318        | 0.4587 | 200  | 0.5122          | -1.1906        | -2.2306          | 0.7284             | 1.0400          | -469.5803      | -404.1460    | 2.4483          | 1.3448        |
| 0.5178        | 0.5734 | 250  | 0.5029          | -1.4402        | -2.5615          | 0.7284             | 1.1212          | -502.6709      | -429.1149    | 2.5336          | 1.3215        |
| 0.519         | 0.6881 | 300  | 0.4985          | -1.4880        | -2.6823          | 0.7371             | 1.1943          | -514.7540      | -433.8906    | 2.6886          | 1.3895        |
| 0.5137        | 0.8028 | 350  | 0.4931          | -1.6128        | -2.8601          | 0.7328             | 1.2473          | -532.5296      | -446.3658    | 3.1580          | 1.8716        |
| 0.5033        | 0.9174 | 400  | 0.4931          | -1.6483        | -2.9482          | 0.7414             | 1.2999          | -541.3424      | -449.9160    | 3.3584          | 2.0773        |


### Framework versions

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