---
license: mit
base_model: microsoft/Phi-3-mini-128k-instruct
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- princeton-nlp/llama3-ultrafeedback
model-index:
- name: phi-3-mini-128k-instruct-simpo-lr-5e-07-gamma-1.5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Description
This model was trained as part of the Reinforcement Learning - 24 project at Peking University, focusing on [simpo].

## Authors
- Ejafa Bassam
- Yaroslav Ponomarenko

# phi-3-mini-128k-instruct-simpo-lr-5e-07-gamma-1.5

This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the princeton-nlp/llama3-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6226
- Rewards/chosen: -2.2430
- Rewards/rejected: -2.6527
- Rewards/accuracies: 0.625
- Rewards/margins: 0.4097
- Logps/rejected: -1.0611
- Logps/chosen: -0.8972
- Logits/rejected: 2.0148
- Logits/chosen: 2.0096

## 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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.6417        | 0.8549 | 400  | 1.6236          | -2.2390        | -2.6457          | 0.6210             | 0.4067          | -1.0583        | -0.8956      | 2.0190          | 2.0146        |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1