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---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: phi-2-gpo-renew2-b0.01-log-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-b0.01-log-i0
This model is a fine-tuned version of [lole25/phi-2-sft-lora-ultrachat](https://huggingface.co/lole25/phi-2-sft-lora-ultrachat) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6909
- Rewards/chosen: -0.0288
- Rewards/rejected: -0.0865
- Rewards/accuracies: 0.6270
- Rewards/margins: 0.0577
- Logps/rejected: -252.4614
- Logps/chosen: -280.4224
- Logits/rejected: 1.0251
- Logits/chosen: 0.9229
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6931 | 0.03 | 100 | 0.6931 | -0.0003 | -0.0006 | 0.4515 | 0.0003 | -243.8745 | -277.5758 | 1.0631 | 0.9710 |
| 0.693 | 0.05 | 200 | 0.6929 | 0.0028 | -0.0017 | 0.5885 | 0.0046 | -243.9904 | -277.2661 | 1.0632 | 0.9705 |
| 0.6926 | 0.08 | 300 | 0.6925 | 0.0100 | -0.0055 | 0.6260 | 0.0155 | -244.3642 | -276.5485 | 1.0488 | 0.9545 |
| 0.6916 | 0.1 | 400 | 0.6920 | 0.0057 | -0.0240 | 0.6340 | 0.0297 | -246.2157 | -276.9778 | 0.9930 | 0.8978 |
| 0.6913 | 0.13 | 500 | 0.6917 | -0.0320 | -0.0687 | 0.6310 | 0.0366 | -250.6851 | -280.7516 | 0.9188 | 0.8239 |
| 0.6916 | 0.16 | 600 | 0.6915 | -0.0605 | -0.1045 | 0.6215 | 0.0440 | -254.2614 | -283.5969 | 0.9507 | 0.8586 |
| 0.6911 | 0.18 | 700 | 0.6914 | -0.0360 | -0.0798 | 0.6260 | 0.0438 | -251.7944 | -281.1486 | 0.9765 | 0.8818 |
| 0.6915 | 0.21 | 800 | 0.6913 | -0.0433 | -0.0906 | 0.6240 | 0.0473 | -252.8779 | -281.8777 | 0.9965 | 0.9022 |
| 0.691 | 0.24 | 900 | 0.6912 | -0.0529 | -0.1055 | 0.6245 | 0.0526 | -254.3653 | -282.8321 | 1.0206 | 0.9266 |
| 0.6913 | 0.26 | 1000 | 0.6912 | -0.0397 | -0.0905 | 0.6290 | 0.0507 | -252.8640 | -281.5216 | 1.0170 | 0.9216 |
| 0.6912 | 0.29 | 1100 | 0.6912 | -0.0550 | -0.1016 | 0.625 | 0.0466 | -253.9782 | -283.0510 | 1.0190 | 0.9244 |
| 0.6902 | 0.31 | 1200 | 0.6912 | -0.0570 | -0.1101 | 0.6230 | 0.0531 | -254.8289 | -283.2487 | 1.0101 | 0.9164 |
| 0.6912 | 0.34 | 1300 | 0.6911 | -0.0234 | -0.0732 | 0.6130 | 0.0498 | -251.1342 | -279.8864 | 1.0357 | 0.9401 |
| 0.6914 | 0.37 | 1400 | 0.6911 | -0.0157 | -0.0634 | 0.6295 | 0.0477 | -250.1540 | -279.1180 | 1.0311 | 0.9342 |
| 0.6919 | 0.39 | 1500 | 0.6910 | -0.0502 | -0.1023 | 0.6320 | 0.0521 | -254.0441 | -282.5649 | 1.0137 | 0.9161 |
| 0.6912 | 0.42 | 1600 | 0.6910 | -0.0349 | -0.0862 | 0.6320 | 0.0513 | -252.4398 | -281.0401 | 1.0315 | 0.9320 |
| 0.6905 | 0.44 | 1700 | 0.6910 | -0.0530 | -0.1089 | 0.6325 | 0.0559 | -254.7030 | -282.8433 | 1.0088 | 0.9100 |
| 0.6901 | 0.47 | 1800 | 0.6910 | -0.0409 | -0.0984 | 0.6225 | 0.0575 | -253.6523 | -281.6338 | 1.0314 | 0.9324 |
| 0.6902 | 0.5 | 1900 | 0.6910 | -0.0326 | -0.0895 | 0.6215 | 0.0569 | -252.7657 | -280.8078 | 1.0212 | 0.9226 |
| 0.6919 | 0.52 | 2000 | 0.6910 | -0.0239 | -0.0768 | 0.6275 | 0.0529 | -251.4911 | -279.9320 | 1.0252 | 0.9259 |
| 0.6919 | 0.55 | 2100 | 0.6909 | -0.0381 | -0.0926 | 0.6345 | 0.0545 | -253.0794 | -281.3606 | 1.0476 | 0.9477 |
| 0.6917 | 0.58 | 2200 | 0.6909 | -0.0421 | -0.0985 | 0.6325 | 0.0564 | -253.6693 | -281.7611 | 1.0407 | 0.9399 |
| 0.6909 | 0.6 | 2300 | 0.6909 | -0.0318 | -0.0861 | 0.6335 | 0.0543 | -252.4272 | -280.7285 | 1.0408 | 0.9399 |
| 0.6903 | 0.63 | 2400 | 0.6909 | -0.0296 | -0.0850 | 0.6360 | 0.0553 | -252.3121 | -280.5100 | 1.0219 | 0.9198 |
| 0.6908 | 0.65 | 2500 | 0.6909 | -0.0373 | -0.0959 | 0.6330 | 0.0586 | -253.4011 | -281.2754 | 1.0213 | 0.9196 |
| 0.6907 | 0.68 | 2600 | 0.6909 | -0.0424 | -0.1023 | 0.6295 | 0.0599 | -254.0473 | -281.7884 | 1.0173 | 0.9161 |
| 0.6905 | 0.71 | 2700 | 0.6909 | -0.0353 | -0.0938 | 0.6310 | 0.0585 | -253.1964 | -281.0736 | 1.0139 | 0.9119 |
| 0.692 | 0.73 | 2800 | 0.6909 | -0.0327 | -0.0894 | 0.6305 | 0.0567 | -252.7526 | -280.8156 | 1.0163 | 0.9141 |
| 0.6906 | 0.76 | 2900 | 0.6909 | -0.0334 | -0.0904 | 0.6295 | 0.0570 | -252.8527 | -280.8846 | 1.0123 | 0.9098 |
| 0.6904 | 0.79 | 3000 | 0.6909 | -0.0312 | -0.0890 | 0.6295 | 0.0579 | -252.7167 | -280.6625 | 1.0147 | 0.9123 |
| 0.6905 | 0.81 | 3100 | 0.6909 | -0.0301 | -0.0877 | 0.6330 | 0.0576 | -252.5846 | -280.5529 | 1.0175 | 0.9147 |
| 0.6919 | 0.84 | 3200 | 0.6909 | -0.0301 | -0.0878 | 0.6305 | 0.0577 | -252.6000 | -280.5576 | 1.0176 | 0.9154 |
| 0.69 | 0.86 | 3300 | 0.6909 | -0.0266 | -0.0839 | 0.6285 | 0.0573 | -252.2050 | -280.2096 | 1.0212 | 0.9186 |
| 0.689 | 0.89 | 3400 | 0.6909 | -0.0289 | -0.0867 | 0.6280 | 0.0578 | -252.4849 | -280.4384 | 1.0223 | 0.9202 |
| 0.6901 | 0.92 | 3500 | 0.6909 | -0.0290 | -0.0869 | 0.6260 | 0.0579 | -252.5046 | -280.4475 | 1.0239 | 0.9216 |
| 0.6914 | 0.94 | 3600 | 0.6909 | -0.0288 | -0.0865 | 0.6290 | 0.0577 | -252.4631 | -280.4258 | 1.0244 | 0.9221 |
| 0.6914 | 0.97 | 3700 | 0.6909 | -0.0289 | -0.0864 | 0.6320 | 0.0576 | -252.4591 | -280.4350 | 1.0240 | 0.9216 |
| 0.6917 | 0.99 | 3800 | 0.6909 | -0.0287 | -0.0866 | 0.6320 | 0.0579 | -252.4790 | -280.4204 | 1.0246 | 0.9221 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2 |