Update README.md

README.md

@@ -1,67 +1,27 @@
 ---
-license: llama3.1
-base_model: meta-llama/Llama-3.1-8B-Instruct
-tags:
-- alignment-handbook
-- generated_from_trainer
-datasets:
-- JunxiongWang/sftdatasetv3
-model-index:
-- name: Llama-Mamba-3.1-8B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0
-  results: []
+license: apache-2.0
 ---
 
-<!-- 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. -->
-
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/junxiong12/huggingface/runs/vtbgj6vc)
-# Llama-Mamba-3.1-8B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0
-
-This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the JunxiongWang/sftdatasetv3 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 242.9601
-
-## 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: 2e-05
-- train_batch_size: 2
-- eval_batch_size: 4
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
-- 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: 0.01
-- num_epochs: 1
-
-### Training results
-
-| Training Loss | Epoch  | Step  | Validation Loss |
-|:-------------:|:------:|:-----:|:---------------:|
-| 220.5766      | 1.0000 | 51995 | 242.9601        |
-
-
-### Framework versions
-
-- Transformers 4.43.1
-- Pytorch 2.1.1+cu118
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+Zero-shot results when using the [Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) as the teacher model, and the [Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) as the initialized model
+
+| Task                | Llama-3.1-8B-Instruct | Llama3.1-Mamba-8B-distill | Llama3.1-Mamba-8B-dpo | Llama3.1-Mamba2-8B-distill | Llama3.1-Mamba-8B-dpo |
+|---------------------|-----------------------|--------------------------|-----------------------|---------------------------|-----------------------|
+| arc_challenge       | 0.552                 | 0.5384                   | 0.5657                | 0.5265                    | 0.5973                |
+| arc_easy            | 0.8178                | 0.8224                   | 0.8401                | 0.822                     | 0.8481                |
+| hellaswag           | 0.7921                | 0.7591                   | 0.7736                | 0.7536                    | 0.7969                |
+| mmlu (0 shot)       | 0.6812                | 0.6213                   | 0.636                 | 0.6101                    | 0.5974                |
+| openbookqa          | 0.432                 | 0.428                    | 0.442                 | 0.416                     | 0.44                  |
+| piqa                | 0.8079                | 0.7933                   | 0.8041                | 0.7889                    | 0.8003                |
+| pubmedqa            | 0.752                 | 0.72                     | 0.744                 | 0.726                     | 0.746                 |
+| race                | 0.4478                | 0.4211                   | 0.4344                | 0.4211                    | 0.4612                |
+| winogrande          | 0.7388                | 0.7277                   | 0.738                 | 0.7174                    | 0.7411                |
+| truthful            | 0.4267                | 0.4002                   | 0.4607                | 0.4031                    | 0.5022                |
+
+```
+@article{junxiongdaniele2024mambainllama,
+  title   = {The Mamba in the Llama: Distilling and Accelerating Hybrid Models},
+  author  = {Junxiong Wang and Daniele Paliotta and Avner May and Alexander M. Rush and Tri Dao},
+  journal = {arXiv preprint arXiv:2408.15237},
+  year    = {2024}
+}
+```