Update README.md

README.md

@@ -1,64 +1,72 @@
 ---
-license: llama3
-base_model: ZhangShenao/0.0001_1SELM_Llama_iter_1
+license: mit
+base_model: ZhangShenao/SELM-Llama-3-8B-Instruct-iter-1
 tags:
 - alignment-handbook
-- trl
 - dpo
-- generated_from_trainer
 - trl
-- dpo
-- generated_from_trainer
+- selm
 datasets:
-- updated
-- original
+- HuggingFaceH4/ultrafeedback_binarized
 model-index:
-- name: 0.0001_1SELM_Llama_iter_2
+- name: SELM-Llama-3-8B-Instruct-iter-2
   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. -->
 
-# 0.0001_1SELM_Llama_iter_2
 
-This model is a fine-tuned version of [ZhangShenao/0.0001_1SELM_Llama_iter_1](https://huggingface.co/ZhangShenao/0.0001_1SELM_Llama_iter_1) on the updated and the original datasets.
+
+Self-Exploring Language Models: Active Preference Elicitation for Online Alignment.
+
+
+
+# SELM-Llama-3-8B-Instruct-iter-2
+
+
+
+This model is a fine-tuned version of [ZhangShenao/SELM-Llama-3-8B-Instruct-iter-1](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-1) using synthetic data based on on the HuggingFaceH4/ultrafeedback_binarized dataset.
+
+
 
 ## Model description
 
-More information needed
 
-## Intended uses & limitations
 
-More information needed
+- Model type: A 8B parameter Llama3-instruct-based Self-Exploring Language Models (SELM).
+- License: MIT
+
+
 
-## Training and evaluation data
+## Results
 
-More information needed
 
-## Training procedure
+
+|                                        | AlpacaEval 2.0 (LC WR) | MT-Bench (Average) |
+|----------------------------------------|------------------------|--------------------|
+| [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)  |    &emsp; &emsp; &emsp;&emsp;         24.31         |  &emsp; &emsp; &emsp;         7.93       |
+| [SELM-Llama-3-8B-Instruct-iter-1](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-1) |    &emsp; &emsp; &emsp;&emsp;         32.02         |  &emsp; &emsp; &emsp;         7.92       |
+| [SELM-Llama-3-8B-Instruct-iter-2](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-2) |    &emsp; &emsp; &emsp;&emsp;         35.65         |  &emsp; &emsp; &emsp;         8.09       |
+| [SELM-Llama-3-8B-Instruct-iter-3](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-3)  |    &emsp; &emsp; &emsp;&emsp;           33.47          |   &emsp; &emsp; &emsp;         8.29       |
+
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-07
+- alpha: 0.0001
+- beta: 0.01
 - train_batch_size: 4
-- eval_batch_size: 4
 - seed: 42
 - distributed_type: multi-GPU
 - num_devices: 8
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 128
-- total_eval_batch_size: 32
 - 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
-
-
-
 ### Framework versions
 
 - Transformers 4.40.2