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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-dpo-ultrachat-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-dpo-ultrachat-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: 0.6912
- Rewards/chosen: -0.0072
- Rewards/rejected: -0.0111
- Rewards/accuracies: 0.3180
- Rewards/margins: 0.0040
- Logps/rejected: -95.3090
- Logps/chosen: -92.4438
- Logits/rejected: 0.8021
- Logits/chosen: 0.7828
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.693 | 0.21 | 100 | 0.6931 | -0.0005 | -0.0008 | 0.2680 | 0.0004 | -94.2804 | -91.7748 | 0.8176 | 0.7998 |
| 0.6922 | 0.42 | 200 | 0.6924 | -0.0018 | -0.0032 | 0.3020 | 0.0014 | -94.5141 | -91.9068 | 0.8121 | 0.7941 |
| 0.6917 | 0.63 | 300 | 0.6917 | -0.0049 | -0.0077 | 0.3100 | 0.0028 | -94.9659 | -92.2189 | 0.8057 | 0.7870 |
| 0.6905 | 0.84 | 400 | 0.6913 | -0.0070 | -0.0105 | 0.3280 | 0.0036 | -95.2509 | -92.4247 | 0.8012 | 0.7827 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2 |