---
base_model: data/zephyr-7b-sft-full-accumulation2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full-accumulation4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zephyr-7b-dpo-full-accumulation4

This model is a fine-tuned version of [data/zephyr-7b-sft-full-accumulation2](https://huggingface.co/data/zephyr-7b-sft-full-accumulation2) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5032
- Rewards/chosen: -0.9893
- Rewards/rejected: -2.0234
- Rewards/accuracies: 0.7812
- Rewards/margins: 1.0341
- Logps/rejected: -462.7061
- Logps/chosen: -358.6745
- Logits/rejected: 3.3182
- Logits/chosen: 2.7991

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.59          | 0.2093 | 100  | 0.5946          | -0.2826        | -0.6651          | 0.7266             | 0.3825          | -326.8777      | -288.0025    | -2.2764         | -2.3187       |
| 0.5622        | 0.4186 | 200  | 0.5490          | -0.5914        | -1.2367          | 0.7578             | 0.6452          | -384.0357      | -318.8896    | -1.6885         | -1.7635       |
| 0.5069        | 0.6279 | 300  | 0.5186          | -0.9189        | -1.8568          | 0.7773             | 0.9379          | -446.0468      | -351.6352    | 3.7286          | 3.1924        |
| 0.5183        | 0.8373 | 400  | 0.5042          | -1.0384        | -2.0520          | 0.7773             | 1.0136          | -465.5701      | -363.5876    | 3.4727          | 2.9519        |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1