---
base_model: JunxiongWang/mamba_0_875_sft
tags:
- mamba
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: mamba_0_875_dpo_ep3
  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. -->

# mamba_0_875_dpo_ep3

This model is a fine-tuned version of [JunxiongWang/mamba_0_875_sft](https://huggingface.co/JunxiongWang/mamba_0_875_sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6922
- Rewards/chosen: -3.9752
- Rewards/rejected: -6.3998
- Rewards/accuracies: 0.7852
- Rewards/margins: 2.4245
- Logps/rejected: -333.8416
- Logps/chosen: -307.0094
- Logits/rejected: -2.4971
- Logits/chosen: -2.5509

## 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
- total_train_batch_size: 32
- 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1219        | 1.0466 | 2000 | 0.5598          | -1.2751        | -2.5954          | 0.7539             | 1.3204          | -295.7982      | -280.0076    | -2.6264         | -2.6813       |
| 0.0099        | 2.0931 | 4000 | 0.6922          | -3.9752        | -6.3998          | 0.7852             | 2.4245          | -333.8416      | -307.0094    | -2.4971         | -2.5509       |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1

[MambaInLlama](arxiv.org/abs/2408.15237)

```
@article{junxiongdaniele2024mambainllama,
  title   = {The Mamba in the Llama: Distilling and Accelerating Hybrid Models},
  author  = {Junxiong Wang and Daniele Paliotta and Avner May and Alexander M. Rush and Tri Dao},
  journal = {arXiv preprint arXiv:2408.15237},
  year    = {2024}
}
```