---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/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-uf-dpo-2e
  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-uf-dpo-2e

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 HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5016
- Rewards/chosen: -1.5911
- Rewards/rejected: -2.8172
- Rewards/accuracies: 0.7695
- Rewards/margins: 1.2260
- Logps/rejected: -544.3789
- Logps/chosen: -421.7447
- Logits/rejected: 2.2404
- Logits/chosen: 1.4759

## 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: 4
- total_train_batch_size: 256
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5692        | 0.4184 | 100  | 0.5671          | -0.3691        | -0.9295          | 0.7344             | 0.5604          | -355.6129      | -299.5389    | -1.1363         | -1.3128       |
| 0.5056        | 0.8368 | 200  | 0.5104          | -0.9550        | -1.8507          | 0.7852             | 0.8957          | -447.7286      | -358.1263    | 1.4954          | 0.9604        |
| 0.3744        | 1.2552 | 300  | 0.5120          | -1.3455        | -2.5618          | 0.7617             | 1.2163          | -518.8406      | -397.1791    | 1.8527          | 0.9871        |
| 0.351         | 1.6736 | 400  | 0.5019          | -1.5195        | -2.7388          | 0.7695             | 1.2193          | -536.5389      | -414.5813    | 2.1782          | 1.4005        |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1