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---
license: other
license_name: microsoft-research-license
license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: Yhyu13/phi-2-sft-alpaca_gpt4_en-ep1
model-index:
- name: phi-2-sft-alpaca_gpt4_en-ep1-dpo-comparison_gpt4_en-ep1-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-sft-alpaca_gpt4_en-ep1-dpo-comparison_gpt4_en-ep1-lora
This model is a fine-tuned version of [Yhyu13/phi-2-sft-alpaca_gpt4_en-ep1](https://huggingface.co/Yhyu13/phi-2-sft-alpaca_gpt4_en-ep1) on the comparison_gpt4_en dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0168
- Rewards/chosen: -1.5750
- Rewards/rejected: -11.4002
- Rewards/accuracies: 0.9956
- Rewards/margins: 9.8253
- Logps/rejected: -142.2352
- Logps/chosen: -139.5300
- Logits/rejected: 0.6066
- Logits/chosen: 0.9744
## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0534 | 0.24 | 1000 | 0.0217 | -1.6714 | -10.2359 | 0.9945 | 8.5645 | -130.5921 | -140.4941 | 0.3064 | 0.5735 |
| 0.0182 | 0.49 | 2000 | 0.0175 | -1.5469 | -10.9602 | 0.9951 | 9.4133 | -137.8349 | -139.2487 | 0.6230 | 1.0709 |
| 0.0162 | 0.73 | 3000 | 0.0171 | -1.5517 | -11.4444 | 0.9962 | 9.8927 | -142.6772 | -139.2976 | 0.6325 | 1.0048 |
| 0.0154 | 0.98 | 4000 | 0.0168 | -1.5741 | -11.4004 | 0.9956 | 9.8262 | -142.2364 | -139.5214 | 0.6051 | 0.9729 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0 |