add models

README.md

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-base_model: /data/junxiong/Llama-Mamba-3.2-3B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0-update/
-tags:
-- alignment-handbook
-- generated_from_trainer
-datasets:
-- HuggingFaceH4/ultrafeedback_binarized
-- HuggingFaceH4/orca_dpo_pairs
-- JunxiongWang/llama3-ultrafeedback-armorm
-model-index:
-- name: Llama-Mamba-3.2-3B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0-update-dpo-short
-  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. -->
-
-[<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/together-research/huggingface/runs/lwnimjip)
-# Llama-Mamba-3.2-3B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0-update-dpo-short
-
-This model is a fine-tuned version of [/data/junxiong/Llama-Mamba-3.2-3B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0-update/](https://huggingface.co//data/junxiong/Llama-Mamba-3.2-3B-teacher-Llama-3.1-70B-Instruct-kl1.0-ce0.0-update/) on the HuggingFaceH4/ultrafeedback_binarized, the HuggingFaceH4/orca_dpo_pairs and the JunxiongWang/llama3-ultrafeedback-armorm datasets.
-It achieves the following results on the evaluation set:
-- Loss: 0.4802
-- Rewards/chosen: -2.0035
-- Rewards/rejected: -4.1751
-- Rewards/accuracies: 0.7929
-- Rewards/margins: 2.1716
-- Logps/rejected: -691.1746
-- Logps/chosen: -472.6584
-- Logits/rejected: -1.5357
-- Logits/chosen: -1.5952
-
-## 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-07
-- train_batch_size: 4
-- eval_batch_size: 8
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- total_train_batch_size: 32
-- total_eval_batch_size: 64
-- 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 |
-|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.5034        | 0.4798 | 2000 | 0.4988          | -1.5060        | -3.1448          | 0.7982             | 1.6388          | -588.1365      | -422.9025    | -1.5466         | -1.5856       |
-| 0.4894        | 0.9597 | 4000 | 0.4802          | -2.0035        | -4.1751          | 0.7929             | 2.1716          | -691.1746      | -472.6584    | -1.5357         | -1.5952       |
-
-
-### Framework versions
-
-- Transformers 4.43.1
-- Pytorch 2.1.1+cu118
-- Datasets 2.20.0
-- Tokenizers 0.19.1