peft tensorboard safetensors phi alignment-handbook generated_from_trainer trl dpo custom_code dataset:HuggingFaceH4/ultrafeedback_binarized base_model:microsoft/phi-2 license:mit region:us
---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: microsoft/phi-2
model-index:
- name: phi-2-ipo-ultrafeedback-lora
  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. -->

# phi-2-ipo-ultrafeedback-lora

This model is a fine-tuned version of [lole25/phi-2-sft-ultrachat-lora](https://huggingface.co/lole25/phi-2-sft-ultrachat-lora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 2156.2256
- Rewards/chosen: -0.1105
- Rewards/rejected: -0.1771
- Rewards/accuracies: 0.6940
- Rewards/margins: 0.0666
- Logps/rejected: -249.1476
- Logps/chosen: -271.2955
- Logits/rejected: 0.7668
- Logits/chosen: 0.6624

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2494.2439     | 0.21  | 100  | 2494.1194       | -0.0001        | -0.0010          | 0.5480             | 0.0009          | -231.5405      | -260.2577    | 0.9164          | 0.8142        |
| 2425.7957     | 0.42  | 200  | 2420.3296       | -0.0052        | -0.0154          | 0.6560             | 0.0101          | -232.9728      | -260.7673    | 0.9218          | 0.8183        |
| 2310.102      | 0.63  | 300  | 2309.9451       | -0.0300        | -0.0576          | 0.6680             | 0.0276          | -237.1959      | -263.2440    | 0.9088          | 0.8041        |
| 2159.0707     | 0.84  | 400  | 2236.2759       | -0.0634        | -0.1085          | 0.6840             | 0.0451          | -242.2857      | -266.5839    | 0.8637          | 0.7578        |
| 2176.8641     | 1.05  | 500  | 2197.5420       | -0.0903        | -0.1463          | 0.6980             | 0.0560          | -246.0634      | -269.2716    | 0.8180          | 0.7125        |
| 2066.3285     | 1.26  | 600  | 2177.3389       | -0.1014        | -0.1628          | 0.6960             | 0.0614          | -247.7128      | -270.3855    | 0.7927          | 0.6879        |
| 2119.5369     | 1.47  | 700  | 2166.3855       | -0.1054        | -0.1702          | 0.6960             | 0.0648          | -248.4533      | -270.7824    | 0.7771          | 0.6726        |
| 2096.7854     | 1.67  | 800  | 2159.7104       | -0.1091        | -0.1756          | 0.6960             | 0.0665          | -248.9965      | -271.1501    | 0.7684          | 0.6641        |
| 2094.5041     | 1.88  | 900  | 2158.6299       | -0.1103        | -0.1768          | 0.6980             | 0.0665          | -249.1140      | -271.2745    | 0.7690          | 0.6646        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2