---
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-dpo-full-ultrabin-amazon
  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-ultrabin-amazon

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: 0.6914
- Rewards/chosen: 0.0
- Rewards/rejected: 0.0
- Rewards/accuracies: 0.0
- Rewards/margins: 0.0
- Logps/rejected: -2352.0
- Logps/chosen: -2624.0
- Logits/rejected: -1.5781
- Logits/chosen: -1.5781

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6914        | 0.1050 | 50   | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -3024.0        | -3440.0      | -2.4844         | -2.5          |
| 0.6914        | 0.2101 | 100  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2544.0        | -2880.0      | -2.0312         | -2.0469       |
| 0.6914        | 0.3151 | 150  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2432.0        | -2736.0      | -1.5938         | -1.5859       |
| 0.6914        | 0.4202 | 200  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2384.0        | -2688.0      | -1.6875         | -1.6875       |
| 0.6914        | 0.5252 | 250  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2352.0        | -2640.0      | -1.7031         | -1.7031       |
| 0.6914        | 0.6303 | 300  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2336.0        | -2624.0      | -1.6797         | -1.6719       |
| 0.6914        | 0.7353 | 350  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2352.0        | -2640.0      | -1.6016         | -1.6016       |
| 0.6914        | 0.8403 | 400  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2368.0        | -2640.0      | -1.5781         | -1.5781       |
| 0.6914        | 0.9454 | 450  | 0.6914          | 0.0            | 0.0              | 0.0                | 0.0             | -2352.0        | -2624.0      | -1.5781         | -1.5781       |


### Framework versions

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