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-gpo-ultrachat-lora-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# phi-2-gpo-ultrachat-lora-2

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: 0.0093
- Rewards/chosen: -0.0154
- Rewards/rejected: -0.0218
- Rewards/accuracies: 0.3500
- Rewards/margins: 0.0064
- Logps/rejected: -96.3794
- Logps/chosen: -93.2678
- Logits/rejected: 0.7520
- Logits/chosen: 0.7332

## 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.01          | 1.04  | 100  | 0.8011        | 0.8188          | -91.7671     | -94.2623       | 0.0100          | 0.25               | -0.0004        | 0.0003          | -0.0007          |
| 0.0098        | 0.42  | 200  | 0.0098        | -0.0018         | -0.0032      | 0.3060         | 0.0015          | -94.5191           | -91.9032       | 0.8107          | 0.7928           |
| 0.0095        | 0.63  | 300  | 0.0096        | -0.0058         | -0.0088      | 0.3060         | 0.0030          | -95.0819           | -92.3092       | 0.7982          | 0.7800           |
| 0.0091        | 0.84  | 400  | 0.0094        | -0.0110         | -0.0157      | 0.3340         | 0.0047          | -95.7642           | -92.8250       | 0.7753          | 0.7565           |
| 0.0094        | 1.05  | 500  | 0.0093        | -0.0132         | -0.0192      | 0.3400         | 0.0060          | -96.1150           | -93.0463       | 0.7679          | 0.7492           |
| 0.0093        | 1.26  | 600  | 0.0093        | -0.0144         | -0.0207      | 0.3440         | 0.0063          | -96.2631           | -93.1677       | 0.7578          | 0.7383           |
| 0.009         | 1.47  | 700  | 0.0093        | -0.0152         | -0.0212      | 0.3480         | 0.0060          | -96.3198           | -93.2491       | 0.7545          | 0.7355           |
| 0.009         | 1.67  | 800  | 0.0093        | -0.0155         | -0.0218      | 0.3420         | 0.0063          | -96.3791           | -93.2749       | 0.7523          | 0.7328           |
| 0.0091        | 1.88  | 900  | 0.0093        | -0.0156         | -0.0218      | 0.3480         | 0.0063          | -96.3809           | -93.2841       | 0.7515          | 0.7320           |


### Framework versions

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