---
license: other
base_model: stabilityai/stablelm-2-zephyr-1_6b
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: slm-2-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. -->

# slm-2-dpo-full

This model is a fine-tuned version of [stabilityai/stablelm-2-zephyr-1_6b](https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 31.9894
- Rewards/chosen: 0.0244
- Rewards/rejected: 0.0188
- Rewards/accuracies: 0.5234
- Rewards/margins: 0.0057
- Logps/rejected: -2491.7576
- Logps/chosen: -2806.6704
- Logits/rejected: -1.6239
- Logits/chosen: -1.6845

## 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: 5
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 80
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 16.8403       | 0.13  | 100  | 19.5118         | 0.0256         | 0.0173           | 0.5273             | 0.0082          | -2491.9011     | -2806.5552   | -1.6068         | -1.6730       |
| 28.1241       | 0.26  | 200  | 32.5175         | 0.0085         | -0.0039          | 0.5234             | 0.0124          | -2494.0195     | -2808.2581   | -1.6183         | -1.6812       |
| 84.7591       | 0.39  | 300  | 47.8043         | 0.0297         | 0.0136           | 0.5391             | 0.0161          | -2492.2703     | -2806.1406   | -1.5968         | -1.6601       |
| 40.7835       | 0.52  | 400  | 30.6722         | 0.0168         | -0.0029          | 0.5547             | 0.0197          | -2493.9204     | -2807.4263   | -1.6288         | -1.6917       |
| 36.2204       | 0.65  | 500  | 31.2202         | 0.0303         | 0.0209           | 0.5352             | 0.0095          | -2491.5447     | -2806.0762   | -1.6236         | -1.6843       |
| 99.7738       | 0.78  | 600  | 33.7403         | 0.0476         | 0.0372           | 0.5391             | 0.0104          | -2489.9089     | -2804.3484   | -1.6222         | -1.6827       |
| 41.8506       | 0.92  | 700  | 32.9133         | 0.0301         | 0.0195           | 0.5547             | 0.0106          | -2491.6851     | -2806.1006   | -1.6211         | -1.6823       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.0+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2