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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-ipo-ultrafeedback-lora
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-ultrafeedback-lora
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: 2156.2256
- Rewards/chosen: -0.1105
- Rewards/rejected: -0.1771
- Rewards/accuracies: 0.6940
- Rewards/margins: 0.0666
- Logps/rejected: -249.1476
- Logps/chosen: -271.2955
- Logits/rejected: 0.7668
- Logits/chosen: 0.6624
## 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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2494.2439 | 0.21 | 100 | 2494.1194 | -0.0001 | -0.0010 | 0.5480 | 0.0009 | -231.5405 | -260.2577 | 0.9164 | 0.8142 |
| 2425.7957 | 0.42 | 200 | 2420.3296 | -0.0052 | -0.0154 | 0.6560 | 0.0101 | -232.9728 | -260.7673 | 0.9218 | 0.8183 |
| 2310.102 | 0.63 | 300 | 2309.9451 | -0.0300 | -0.0576 | 0.6680 | 0.0276 | -237.1959 | -263.2440 | 0.9088 | 0.8041 |
| 2159.0707 | 0.84 | 400 | 2236.2759 | -0.0634 | -0.1085 | 0.6840 | 0.0451 | -242.2857 | -266.5839 | 0.8637 | 0.7578 |
| 2176.8641 | 1.05 | 500 | 2197.5420 | -0.0903 | -0.1463 | 0.6980 | 0.0560 | -246.0634 | -269.2716 | 0.8180 | 0.7125 |
| 2066.3285 | 1.26 | 600 | 2177.3389 | -0.1014 | -0.1628 | 0.6960 | 0.0614 | -247.7128 | -270.3855 | 0.7927 | 0.6879 |
| 2119.5369 | 1.47 | 700 | 2166.3855 | -0.1054 | -0.1702 | 0.6960 | 0.0648 | -248.4533 | -270.7824 | 0.7771 | 0.6726 |
| 2096.7854 | 1.67 | 800 | 2159.7104 | -0.1091 | -0.1756 | 0.6960 | 0.0665 | -248.9965 | -271.1501 | 0.7684 | 0.6641 |
| 2094.5041 | 1.88 | 900 | 2158.6299 | -0.1103 | -0.1768 | 0.6980 | 0.0665 | -249.1140 | -271.2745 | 0.7690 | 0.6646 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2 |