---
base_model: data/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
  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

This model is a fine-tuned version of [data/zephyr-7b-sft-full](https://huggingface.co/data/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5257
- Rewards/chosen: -0.6523
- Rewards/rejected: -1.4719
- Rewards/accuracies: 0.7695
- Rewards/margins: 0.8195
- Logps/rejected: -411.0257
- Logps/chosen: -329.0598
- Logits/rejected: 0.9901
- Logits/chosen: 0.7049

## 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: 42
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5992        | 0.2092 | 100  | 0.5956          | -0.2932        | -0.6564          | 0.7148             | 0.3632          | -329.4821      | -293.1491    | -2.2402         | -2.2843       |
| 0.57          | 0.4184 | 200  | 0.5591          | -0.3908        | -0.9608          | 0.7422             | 0.5700          | -359.9165      | -302.9073    | -1.6390         | -1.7197       |
| 0.5222        | 0.6276 | 300  | 0.5473          | -0.4814        | -1.1717          | 0.7461             | 0.6902          | -381.0072      | -311.9707    | -1.3133         | -1.4138       |
| 0.5332        | 0.8368 | 400  | 0.5284          | -0.6175        | -1.4117          | 0.7539             | 0.7941          | -405.0050      | -325.5808    | 0.5323          | 0.2839        |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.19.1
- Tokenizers 0.19.1