---
base_model: JunxiongWang/mamba_0_75_sft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: mamba_0_75_dpo_ep3
  results: []
---

Please check [here](https://github.com/jxiw/MambaInLlama/tree/main) for details.

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# mamba_0_75_dpo_ep3

This model is a fine-tuned version of [JunxiongWang/mamba_0_75_sft](https://huggingface.co/JunxiongWang/mamba_0_75_sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7077
- Rewards/chosen: -4.3611
- Rewards/rejected: -7.0013
- Rewards/accuracies: 0.7812
- Rewards/margins: 2.6403
- Logps/rejected: -333.1784
- Logps/chosen: -302.4903
- Logits/rejected: -2.8351
- Logits/chosen: -2.8752

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.1188        | 1.0466 | 2000 | 0.5385          | -1.3137        | -2.8323          | 0.7852             | 1.5186          | -291.4879      | -272.0161    | -2.9057         | -2.9472       |
| 0.0093        | 2.0931 | 4000 | 0.7077          | -4.3611        | -7.0013          | 0.7812             | 2.6403          | -333.1784      | -302.4903    | -2.8351         | -2.8752       |


### Framework versions

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