SELM-Phi
Collection
4 items
•
Updated
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment.
SELM-Phi-3-mini-4k-instruct-iter-3
This model is a fine-tuned version of ZhangShenao/SELM-Phi-3-mini-4k-instruct-iter-2 using synthetic data based on on the HuggingFaceH4/ultrafeedback_binarized dataset.
Model description
- Model type: A 3.8B parameter Phi3-instruct-based Self-Exploring Language Models (SELM).
- License: MIT
Results
| AlpacaEval 2.0 (LC WR) | MT-Bench (Average) | |
|---|---|---|
| SELM-Phi-3-mini-4k-instruct-iter-3 | 27.98 | 8.32 |
| SELM-Phi-3-mini-4k-instruct-iter-2 | 26.79 | 8.44 |
| SELM-Phi-3-mini-4k-instruct-iter-1 | 27.33 | 8.37 |
| Phi-3-mini-4k-instruct | 23.05 | 8.12 |
Our model also ranks highly on WildBench! 🔥
Training hyperparameters
The following hyperparameters were used during training:
- alpha: 0.001
- beta: 0.01
- train_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- num_epochs: 1
Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
- Downloads last month
- 26
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for ZhangShenao/SELM-Phi-3-mini-4k-instruct-iter-3
Base model
microsoft/Phi-3-mini-4k-instruct