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---
license: mit
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
base_model: microsoft/phi-2
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: phi-2-ipo-test-iter-0
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-test-iter-0
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: 2546.4375
- Rewards/chosen: -0.1591
- Rewards/rejected: -0.1612
- Rewards/accuracies: 0.5220
- Rewards/margins: 0.0021
- Logps/rejected: -249.6534
- Logps/chosen: -272.5227
- Logits/rejected: 0.4171
- Logits/chosen: 0.3526
## 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2477.3281 | 0.32 | 100 | 2500.7156 | -0.0018 | -0.0018 | 0.4930 | -0.0000 | -233.7207 | -256.7978 | 0.8796 | 0.8221 |
| 2224.3488 | 0.64 | 200 | 2499.8904 | -0.0195 | -0.0198 | 0.5015 | 0.0003 | -235.5204 | -258.5673 | 0.8051 | 0.7462 |
| 1898.0719 | 0.96 | 300 | 2505.6912 | -0.0563 | -0.0571 | 0.5140 | 0.0008 | -239.2530 | -262.2491 | 0.6844 | 0.6233 |
| 1879.8852 | 1.28 | 400 | 2516.0835 | -0.0944 | -0.0957 | 0.5200 | 0.0013 | -243.1053 | -266.0533 | 0.5839 | 0.5215 |
| 1917.2811 | 1.6 | 500 | 2527.1995 | -0.1156 | -0.1170 | 0.5115 | 0.0014 | -245.2343 | -268.1747 | 0.5244 | 0.4611 |
| 1799.3824 | 1.92 | 600 | 2534.4292 | -0.1363 | -0.1381 | 0.5210 | 0.0018 | -247.3504 | -270.2482 | 0.4714 | 0.4075 |
| 1751.5762 | 2.24 | 700 | 2531.3550 | -0.1448 | -0.1474 | 0.5180 | 0.0026 | -248.2780 | -271.0988 | 0.4545 | 0.3906 |
| 1711.1711 | 2.56 | 800 | 2536.2451 | -0.1487 | -0.1511 | 0.5145 | 0.0024 | -248.6440 | -271.4834 | 0.4402 | 0.3759 |
| 1894.4447 | 2.88 | 900 | 2542.6299 | -0.1549 | -0.1570 | 0.5235 | 0.0022 | -249.2417 | -272.1000 | 0.4262 | 0.3618 |
| 1798.5389 | 3.2 | 1000 | 2542.7288 | -0.1581 | -0.1604 | 0.5205 | 0.0023 | -249.5780 | -272.4200 | 0.4202 | 0.3559 |
| 1834.9711 | 3.52 | 1100 | 2542.2373 | -0.1586 | -0.1610 | 0.5205 | 0.0024 | -249.6345 | -272.4703 | 0.4177 | 0.3532 |
| 1765.5148 | 3.84 | 1200 | 2546.1714 | -0.1589 | -0.1610 | 0.5220 | 0.0021 | -249.6357 | -272.5010 | 0.4160 | 0.3515 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |