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---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |