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---
base_model: JunxiongWang/mamba_0_5_sft
tags:
- mamba
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: mamba_0_5_dpo_ep3
results: []
---
Please check [here](https://github.com/jxiw/MambaInLlama/tree/main) for details.
<!-- 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_5_dpo_ep3
This model is a fine-tuned version of [JunxiongWang/mamba_0_5_dpo_ep3](https://huggingface.co/JunxiongWang/mamba_0_5_sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7141
- Rewards/chosen: -5.3346
- Rewards/rejected: -8.3118
- Rewards/accuracies: 0.7891
- Rewards/margins: 2.9772
- Logps/rejected: -337.4994
- Logps/chosen: -304.9619
- Logits/rejected: -2.7812
- Logits/chosen: -2.8272
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1171 | 1.0466 | 2000 | 0.5329 | -1.4521 | -2.9272 | 0.7734 | 1.4750 | -283.6535 | -266.1376 | -2.8897 | -2.9362 |
| 0.0086 | 2.0931 | 4000 | 0.7141 | -5.3346 | -8.3118 | 0.7891 | 2.9772 | -337.4994 | -304.9619 | -2.7812 | -2.8272 |
### 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}
}
```
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