Quant for 5.0

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -9,69 +9,127 @@ model-index:
 - name: princeton-nlp/gemma-2-9b-it-SimPO 
   results: []
 license: mit
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of gemma-2-9b-it-SimPO
+# gemma-2-9b-it-SimPO Model Card
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.1.8">turboderp's ExLlamaV2 v0.1.8</a> for quantization.
+SimPO (Simple Preference Optimization) is an offline preference optimization algorithm designed to enhance the training of large language models (LLMs) with preference optimization datasets. SimPO aligns the reward function with the generation likelihood, eliminating the need for a reference model and incorporating a target reward margin to boost performance. Please refer to our [preprint](https://arxiv.org/pdf/2405.14734) and [github repo](https://github.com/princeton-nlp/SimPO) for more details.
 
-<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
+## Model Details
 
-Original model: https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO
+### Model Description
 
-## Prompt format
+We fine-tuned [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm) with the SimPO objective.
 
-```
-<bos><start_of_turn>user
-{system_prompt}
+- **Developed by:** Yu Meng, Mengzhou Xia, Danqi Chen
+- **Model type:** Causal Language Model
+- **License:** gemma
+- **Finetuned from model:** [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
 
-{prompt}<end_of_turn>
-<start_of_turn>model
-<end_of_turn>
-<start_of_turn>model
+- **Repository:** https://github.com/princeton-nlp/SimPO
+- **Paper:** https://arxiv.org/pdf/2405.14734
 
+
+## How to Get Started with the Model
+```
+import torch
+from transformers import pipeline
+
+model_id = "princeton-nlp/gemma-2-9b-it-SimPO"
+
+generator = pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device="cuda",
+)
+outputs = generator([{"role": "user", "content": "What's the difference between llamas and alpacas?"}], do_sample=False, max_new_tokens=200)
+print(outputs[0]['generated_text'])
 ```
 
-## Available sizes
+## Training Details
 
-| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
-| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
-| [8_0](https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2/tree/8_0) | 8.0 | 8.0 | 11.9 GB | 15.9 GB | 21.3 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2/tree/6_5) | 6.5 | 8.0 | 10.4 GB | 14.4 GB | 19.8 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2/tree/5_0) | 5.0 | 6.0 | 8.6 GB | 12.6 GB | 18.0 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2/tree/4_25) | 4.25 | 6.0 | 7.9 GB | 11.9 GB | 17.3 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2/tree/3_5) | 3.5 | 6.0 | 7.1 GB | 11.1 GB | 16.9 GB | Lower quality, only use if you have to. |
+### Training Data
 
-## Download instructions
+We use [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm) as the preference optimization dataset.
 
-With git:
+#### Training Hyperparameters
 
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/gemma-2-9b-it-SimPO-exl2 gemma-2-9b-it-SimPO-exl2-6_5
-```
+The hyperparameters used can be found in the [training script](https://github.com/princeton-nlp/SimPO/blob/main/training_configs/gemma-2-9b-it-simpo.yaml).
 
-With huggingface hub (credit to TheBloke for instructions):
+#### Speeds, Sizes, Times
+
+Fine-tuning the [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm) takes around 100 mins to finish on 8xH100 GPUs.
+
+## Evaluation Results
+
+
+|               models                    | AE2 LC | AE2 WR | AE2 Length |  AH  | AH Length |  GSM | GSM Length | MMLU | MMLU Length |
+|-----------------------------------|:------:|:------:|:----------:|:----:|:---------:|:----:|:----------:|:----:|:-----------:|
+|        [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)       |  51.1  |  38.1  |    1571    | 40.8 |    545    | 87.4 |     395    | 72.7 |     515     |
+|  [princeton-nlp/gemma-2-9b-it-DPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-DPO)  |  67.8  |  65.4  |    2016    | 58.9 |    717    | 88.5 |     392    | 72.2 |     624     |
+| [princeton-nlp/gemma-2-9b-it-SimPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO) |  72.4  |  65.9  |    1833    | 59.1 |    693    | 88.0 |     341    | 72.2 |     441     |
 
-```shell
-pip3 install huggingface-hub
-```
 
-To download a specific branch, use the `--revision` parameter. For example, to download the 6.5 bpw branch:
+## Technical Specifications
 
-Linux:
+### Model Architecture and Objective
 
-```shell
-huggingface-cli download bartowski/gemma-2-9b-it-SimPO-exl2 --revision 6_5 --local-dir gemma-2-9b-it-SimPO-exl2-6_5
+The model architecture is based on [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it). We use the SimPO training objective proposed in our [preprint](https://arxiv.org/pdf/2405.14734).
+
+#### Hardware
+
+We used 8xH100 GPUs for model training.
+
+#### Software
+
+Training was done using the [alignment-handbook](https://github.com/huggingface/alignment-handbook) library.
+
+## Citation
+
+gemma model:
+```
+@article{gemma_2024,
+    title={Gemma},
+    url={https://www.kaggle.com/m/3301},
+    DOI={10.34740/KAGGLE/M/3301},
+    publisher={Kaggle},
+    author={Gemma Team},
+    year={2024}
+}
 ```
 
-Windows (which apparently doesn't like _ in folders sometimes?):
+SimPO paper:
+```
+@article{meng2024simpo,
+  title={{SimPO}: Simple preference optimization with a reference-free reward},
+  author={Meng, Yu and Xia, Mengzhou and Chen, Danqi},
+  journal={arXiv preprint arXiv:2405.14734},
+  year={2024}
+}
+```
 
-```shell
-huggingface-cli download bartowski/gemma-2-9b-it-SimPO-exl2 --revision 6_5 --local-dir gemma-2-9b-it-SimPO-exl2-6.5
+UltraFeedback paper:
+```
+@article{cui2023ultrafeedback,
+  title={{UltraFeedback}: Boosting language models with high-quality feedback},
+  author={Cui, Ganqu and Yuan, Lifan and Ding, Ning and Yao, Guanming and Zhu, Wei and Ni, Yuan and Xie, Guotong and Liu, Zhiyuan and Sun, Maosong},
+  journal={arXiv preprint arXiv:2310.01377},
+  year={2023}
+}
 ```
 
-Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
+ArmoRM paper:
+```
+@article{wang2024interpretable,
+  title={Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts},
+  author={Wang, Haoxiang and Xiong, Wei and Xie, Tengyang and Zhao, Han and Zhang, Tong},
+  journal={arXiv preprint arXiv:2406.12845},
+  year={2024}
+}
+```

all_results.json

@@ -0,0 +1,22 @@
+{
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+    "eval_logits/chosen": -13.382477760314941,
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+    "eval_logps/chosen": -1.8618243932724,
+    "eval_logps/rejected": -2.3445940017700195,
+    "eval_loss": 2.7497549057006836,
+    "eval_rewards/accuracies": 0.7581967115402222,
+    "eval_rewards/chosen": -18.618242263793945,
+    "eval_rewards/margins": 4.82769775390625,
+    "eval_rewards/rejected": -23.445940017700195,
+    "eval_runtime": 69.1462,
+    "eval_samples": 1941,
+    "eval_samples_per_second": 28.071,
+    "eval_steps_per_second": 0.882,
+    "total_flos": 0.0,
+    "train_loss": 3.5518602760889197,
+    "train_runtime": 6148.2375,
+    "train_samples": 59569,
+    "train_samples_per_second": 9.689,
+    "train_steps_per_second": 0.076
+}

config.json

@@ -0,0 +1,45 @@
+{
+    "_name_or_path": "princeton-nlp/gemma-2-9b-it-SimPO",
+    "architectures": [
+        "Gemma2ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_logit_softcapping": 50.0,
+    "bos_token_id": 2,
+    "cache_implementation": "hybrid",
+    "eos_token_id": 1,
+    "final_logit_softcapping": 30.0,
+    "head_dim": 256,
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_activation": "gelu_pytorch_tanh",
+    "hidden_size": 3584,
+    "initializer_range": 0.02,
+    "intermediate_size": 14336,
+    "max_position_embeddings": 8192,
+    "model_type": "gemma2",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 42,
+    "num_key_value_heads": 8,
+    "pad_token_id": 0,
+    "query_pre_attn_scalar": 256,
+    "rms_norm_eps": 1e-06,
+    "rope_theta": 10000.0,
+    "sliding_window": 4096,
+    "sliding_window_size": 4096,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.42.4",
+    "use_cache": true,
+    "vocab_size": 256000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.1.8",
+        "bits": 5.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

eval_results.json

@@ -0,0 +1,16 @@
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+    "eval_rewards/chosen": -18.618242263793945,
+    "eval_rewards/margins": 4.82769775390625,
+    "eval_rewards/rejected": -23.445940017700195,
+    "eval_runtime": 69.1462,
+    "eval_samples": 1941,
+    "eval_samples_per_second": 28.071,
+    "eval_steps_per_second": 0.882
+}

generation_config.json

@@ -0,0 +1,8 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.42.4"
+}

model.safetensors.index.json

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+    "179": {
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+    "180": {
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+    },
+    "181": {
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+      "special": false
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+    "182": {
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+    "183": {
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+    "184": {
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+    "189": {
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+    "190": {
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+    },
+    "191": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "192": {
+      "content": "</h1>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "193": {
+      "content": "</h2>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "194": {
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+      "special": false
+    },
+    "195": {
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+      "normalized": false,
+      "rstrip": false,
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+    },
+    "196": {
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+      "lstrip": false,
+      "normalized": false,
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+    "197": {
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+      "normalized": false,
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+    "199": {
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+      "single_word": false,
+      "special": false
+    },
+    "202": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "203": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "204": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "205": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "206": {
+      "content": "<sup>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "207": {
+      "content": "<code>",
+      "lstrip": false,
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+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "208": {
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+    },
+    "209": {
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+    "210": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+    },
+    "211": {
+      "content": "</i>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "212": {
+      "content": "</u>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "213": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "214": {
+      "content": "</sub>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "215": {
+      "content": "</sup>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "216": {
+      "content": "</code>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": "<bos>",
+  "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] | trim + '\n\n' %}{% set messages = messages[1:] %}{% else %}{% set system_message = '' %}{% endif %}{% for message in messages %}{% if loop.index0 == 0 %}{% set content = system_message + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + content | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "model_max_length": 2048,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 0.9989258861439313,
+    "total_flos": 0.0,
+    "train_loss": 3.5518602760889197,
+    "train_runtime": 6148.2375,
+    "train_samples": 59569,
+    "train_samples_per_second": 9.689,
+    "train_steps_per_second": 0.076
+}

trainer_state.json

@@ -0,0 +1,1437 @@
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