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---
license: mit
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: phi-2-gpo-renew2-i0
  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-renew2-i0

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0346
- Rewards/chosen: -0.0264
- Rewards/rejected: -0.0854
- Rewards/accuracies: 0.6290
- Rewards/margins: 0.0591
- Logps/rejected: -252.3589
- Logps/chosen: -280.1829
- Logits/rejected: 1.0402
- Logits/chosen: 0.9379

## 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
- gradient_accumulation_steps: 4
- total_train_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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0659        | 0.03  | 100  | 0.0536          | -0.0002        | -0.0008          | 0.4745             | 0.0005          | -243.8923      | -277.5683    | 1.0635          | 0.9711        |
| 0.0597        | 0.05  | 200  | 0.0518          | 0.0035         | -0.0015          | 0.5880             | 0.0050          | -243.9651      | -277.1979    | 1.0617          | 0.9688        |
| 0.0564        | 0.08  | 300  | 0.0475          | 0.0104         | -0.0081          | 0.6175             | 0.0185          | -244.6272      | -276.5096    | 1.0440          | 0.9499        |
| 0.0402        | 0.1   | 400  | 0.0438          | 0.0017         | -0.0309          | 0.6325             | 0.0326          | -246.9109      | -277.3771    | 0.9932          | 0.8995        |
| 0.0421        | 0.13  | 500  | 0.0411          | -0.0415        | -0.0810          | 0.6195             | 0.0395          | -251.9139      | -281.6956    | 0.9295          | 0.8362        |
| 0.0439        | 0.16  | 600  | 0.0395          | -0.0701        | -0.1168          | 0.6175             | 0.0468          | -255.5005      | -284.5547    | 0.9520          | 0.8607        |
| 0.0363        | 0.18  | 700  | 0.0390          | -0.0362        | -0.0808          | 0.6310             | 0.0446          | -251.8926      | -281.1619    | 0.9895          | 0.8949        |
| 0.0402        | 0.21  | 800  | 0.0382          | -0.0514        | -0.1006          | 0.6220             | 0.0491          | -253.8720      | -282.6901    | 0.9937          | 0.9001        |
| 0.0381        | 0.24  | 900  | 0.0376          | -0.0554        | -0.1099          | 0.6315             | 0.0545          | -254.8047      | -283.0851    | 1.0465          | 0.9534        |
| 0.0421        | 0.26  | 1000 | 0.0374          | -0.0408        | -0.0930          | 0.6270             | 0.0522          | -253.1114      | -281.6268    | 1.0399          | 0.9448        |
| 0.0393        | 0.29  | 1100 | 0.0370          | -0.0576        | -0.1053          | 0.6285             | 0.0478          | -254.3491      | -283.3031    | 1.0557          | 0.9609        |
| 0.0533        | 0.31  | 1200 | 0.0369          | -0.0606        | -0.1154          | 0.6210             | 0.0548          | -255.3544      | -283.6022    | 1.0368          | 0.9417        |
| 0.0392        | 0.34  | 1300 | 0.0367          | -0.0207        | -0.0714          | 0.6120             | 0.0508          | -250.9576      | -279.6129    | 1.0634          | 0.9660        |
| 0.0432        | 0.37  | 1400 | 0.0367          | -0.0146        | -0.0629          | 0.6260             | 0.0483          | -250.1082      | -279.0112    | 1.0463          | 0.9482        |
| 0.0304        | 0.39  | 1500 | 0.0359          | -0.0523        | -0.1062          | 0.6360             | 0.0539          | -254.4339      | -282.7773    | 1.0471          | 0.9496        |
| 0.0436        | 0.42  | 1600 | 0.0359          | -0.0322        | -0.0845          | 0.6340             | 0.0522          | -252.2616      | -280.7699    | 1.0586          | 0.9585        |
| 0.0405        | 0.44  | 1700 | 0.0355          | -0.0531        | -0.1105          | 0.6335             | 0.0575          | -254.8697      | -282.8529    | 1.0312          | 0.9322        |
| 0.0352        | 0.47  | 1800 | 0.0354          | -0.0369        | -0.0956          | 0.6220             | 0.0586          | -253.3721      | -281.2394    | 1.0533          | 0.9539        |
| 0.0392        | 0.5   | 1900 | 0.0355          | -0.0281        | -0.0860          | 0.6210             | 0.0579          | -252.4193      | -280.3594    | 1.0498          | 0.9508        |
| 0.0368        | 0.52  | 2000 | 0.0354          | -0.0231        | -0.0770          | 0.6300             | 0.0539          | -251.5159      | -279.8615    | 1.0563          | 0.9577        |
| 0.0326        | 0.55  | 2100 | 0.0352          | -0.0360        | -0.0915          | 0.6300             | 0.0555          | -252.9630      | -281.1432    | 1.0751          | 0.9760        |
| 0.0368        | 0.58  | 2200 | 0.0352          | -0.0391        | -0.0965          | 0.6345             | 0.0574          | -253.4691      | -281.4595    | 1.0642          | 0.9640        |
| 0.0315        | 0.6   | 2300 | 0.0351          | -0.0252        | -0.0801          | 0.6330             | 0.0549          | -251.8242      | -280.0628    | 1.0685          | 0.9676        |
| 0.0341        | 0.63  | 2400 | 0.0352          | -0.0240        | -0.0803          | 0.6320             | 0.0563          | -251.8426      | -279.9447    | 1.0420          | 0.9405        |
| 0.0488        | 0.65  | 2500 | 0.0350          | -0.0321        | -0.0918          | 0.6340             | 0.0597          | -252.9968      | -280.7594    | 1.0394          | 0.9378        |
| 0.0279        | 0.68  | 2600 | 0.0349          | -0.0383        | -0.0996          | 0.6315             | 0.0613          | -253.7721      | -281.3765    | 1.0361          | 0.9350        |
| 0.0427        | 0.71  | 2700 | 0.0348          | -0.0312        | -0.0911          | 0.6310             | 0.0600          | -252.9290      | -280.6644    | 1.0336          | 0.9319        |
| 0.0331        | 0.73  | 2800 | 0.0349          | -0.0291        | -0.0872          | 0.6290             | 0.0581          | -252.5369      | -280.4611    | 1.0354          | 0.9335        |
| 0.0415        | 0.76  | 2900 | 0.0349          | -0.0298        | -0.0883          | 0.6315             | 0.0585          | -252.6469      | -280.5276    | 1.0248          | 0.9228        |
| 0.0404        | 0.79  | 3000 | 0.0349          | -0.0268        | -0.0859          | 0.6295             | 0.0590          | -252.4009      | -280.2291    | 1.0305          | 0.9277        |
| 0.0362        | 0.81  | 3100 | 0.0348          | -0.0264        | -0.0849          | 0.6305             | 0.0585          | -252.3079      | -280.1861    | 1.0296          | 0.9270        |
| 0.0412        | 0.84  | 3200 | 0.0348          | -0.0274        | -0.0861          | 0.6260             | 0.0587          | -252.4237      | -280.2876    | 1.0338          | 0.9313        |
| 0.0485        | 0.86  | 3300 | 0.0347          | -0.0242        | -0.0824          | 0.6270             | 0.0582          | -252.0546      | -279.9648    | 1.0359          | 0.9336        |
| 0.0376        | 0.89  | 3400 | 0.0346          | -0.0264        | -0.0854          | 0.6310             | 0.0590          | -252.3589      | -280.1902    | 1.0377          | 0.9354        |
| 0.0352        | 0.92  | 3500 | 0.0346          | -0.0266        | -0.0856          | 0.6260             | 0.0590          | -252.3726      | -280.2037    | 1.0418          | 0.9392        |
| 0.0379        | 0.94  | 3600 | 0.0347          | -0.0263        | -0.0852          | 0.6315             | 0.0589          | -252.3377      | -280.1781    | 1.0414          | 0.9390        |
| 0.0361        | 0.97  | 3700 | 0.0346          | -0.0266        | -0.0856          | 0.6310             | 0.0590          | -252.3741      | -280.2047    | 1.0399          | 0.9377        |
| 0.0298        | 0.99  | 3800 | 0.0347          | -0.0263        | -0.0850          | 0.6275             | 0.0587          | -252.3201      | -280.1767    | 1.0412          | 0.9387        |


### Framework versions

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