bushai
/

sar-i-7b

@@ -186,17 +186,6 @@ model-index:
       url: https://huggingface.co/spaces/lmsys/mt-bench
 ---
-<!-- 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://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png" alt="Zephyr Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
-# Model Card for Zephyr 7B β
-Zephyr is a series of language models that are trained to act as helpful assistants. Zephyr-7B-β is the second model in the series, and is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) that was trained on on a mix of publicly available, synthetic datasets using [Direct Preference Optimization (DPO)](https://arxiv.org/abs/2305.18290). We found that removing the in-built alignment of these datasets boosted performance on [MT Bench](https://huggingface.co/spaces/lmsys/mt-bench) and made the model more helpful. However, this means that model is likely to generate problematic text when prompted to do so. You can find more details in the [technical report](https://arxiv.org/abs/2310.16944).
 ## Model description
 - **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
@@ -204,50 +193,8 @@ Zephyr is a series of language models that are trained to act as helpful assista
 - **License:** MIT
 - **Finetuned from model:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
-### Model Sources
-<!-- Provide the basic links for the model. -->
-- **Repository:** https://github.com/huggingface/alignment-handbook
-- **Demo:** https://huggingface.co/spaces/HuggingFaceH4/zephyr-chat
-- **Chatbot Arena:** Evaluate Zephyr 7B against 10+ LLMs in the LMSYS arena: http://arena.lmsys.org
-## Performance
-At the time of release, Zephyr-7B-β is the highest ranked 7B chat model on the [MT-Bench](https://huggingface.co/spaces/lmsys/mt-bench) and [AlpacaEval](https://tatsu-lab.github.io/alpaca_eval/) benchmarks:
-| Model | Size | Alignment | MT-Bench (score) | AlpacaEval (win rate %) |
-|-------------|-----|----|---------------|--------------|
-| StableLM-Tuned-α | 7B| dSFT |2.75| -|
-| MPT-Chat |  7B |dSFT |5.42| -|
-| Xwin-LMv0.1 | 7B| dPPO| 6.19| 87.83|
-| Mistral-Instructv0.1 | 7B|  - | 6.84 |-|
-| Zephyr-7b-α |7B|  dDPO| 6.88| -|
-| **Zephyr-7b-β** 🪁 | **7B** | **dDPO** | **7.34** | **90.60** |
-| Falcon-Instruct |  40B |dSFT |5.17 |45.71|
-| Guanaco | 65B |  SFT |6.41| 71.80|
-| Llama2-Chat |  70B |RLHF |6.86| 92.66|
-| Vicuna v1.3 |  33B |dSFT |7.12 |88.99|
-| WizardLM v1.0 |  70B |dSFT |7.71 |-|
-| Xwin-LM v0.1 |   70B |dPPO |- |95.57|
-| GPT-3.5-turbo | - |RLHF |7.94 |89.37|
-| Claude 2 |  - |RLHF |8.06| 91.36|
-| GPT-4 |  -| RLHF |8.99| 95.28|
-In particular, on several categories of MT-Bench, Zephyr-7B-β has strong performance compared to larger open models like Llama2-Chat-70B:
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6200d0a443eb0913fa2df7cc/raxvt5ma16d7T23my34WC.png)
-However, on more complex tasks like coding and mathematics, Zephyr-7B-β lags behind proprietary models and more research is needed to close the gap.
 ## Intended uses & limitations
-The model was initially fine-tuned on a filtered and preprocessed of the [`UltraChat`](https://huggingface.co/datasets/stingning/ultrachat) dataset, which contains a diverse range of synthetic dialogues generated by ChatGPT.
-We then further aligned the model with [🤗 TRL's](https://github.com/huggingface/trl) `DPOTrainer` on the [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset, which contains 64k prompts and model completions that are ranked by GPT-4. As a result, the model can be used for chat and you can check out our [demo](https://huggingface.co/spaces/HuggingFaceH4/zephyr-chat) to test its capabilities.
-You can find the datasets used for training Zephyr-7B-β [here](https://huggingface.co/collections/HuggingFaceH4/zephyr-7b-6538c6d6d5ddd1cbb1744a66)
 Here's how you can run the model using the `pipeline()` function from 🤗 Transformers:
 ```python
@@ -279,112 +226,6 @@ print(outputs[0]["generated_text"])
 # Ah, me hearty matey! But yer question be a puzzler! A human cannot eat a helicopter in one sitting, as helicopters are not edible. They be made of metal, plastic, and other materials, not food!
 ```
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-Zephyr-7B-β has not been aligned to human preferences for safety within the RLHF phase or deployed with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so).
-It is also unknown what the size and composition of the corpus was used to train the base model (`mistralai/Mistral-7B-v0.1`), however it is likely to have included a mix of Web data and technical sources like books and code. See the [Falcon 180B model card](https://huggingface.co/tiiuae/falcon-180B#training-data) for an example of this.
-## Training and evaluation data
-During DPO training, this model achieves the following results on the evaluation set:
-- Loss: 0.7496
-- Rewards/chosen: -4.5221
-- Rewards/rejected: -8.3184
-- Rewards/accuracies: 0.7812
-- Rewards/margins: 3.7963
-- Logps/rejected: -340.1541
-- Logps/chosen: -299.4561
-- Logits/rejected: -2.3081
-- Logits/chosen: -2.3531
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 5e-07
-- train_batch_size: 2
-- eval_batch_size: 4
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 16
-- 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: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3.0
-### Training results
-The table below shows the full set of DPO training metrics:
-| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
-|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.6284        | 0.05  | 100  | 0.6098          | 0.0425         | -0.1872          | 0.7344             | 0.2297          | -258.8416      | -253.8099    | -2.7976         | -2.8234       |
-| 0.4908        | 0.1   | 200  | 0.5426          | -0.0279        | -0.6842          | 0.75               | 0.6563          | -263.8124      | -254.5145    | -2.7719         | -2.7960       |
-| 0.5264        | 0.15  | 300  | 0.5324          | 0.0414         | -0.9793          | 0.7656             | 1.0207          | -266.7627      | -253.8209    | -2.7892         | -2.8122       |
-| 0.5536        | 0.21  | 400  | 0.4957          | -0.0185        | -1.5276          | 0.7969             | 1.5091          | -272.2460      | -254.4203    | -2.8542         | -2.8764       |
-| 0.5362        | 0.26  | 500  | 0.5031          | -0.2630        | -1.5917          | 0.7812             | 1.3287          | -272.8869      | -256.8653    | -2.8702         | -2.8958       |
-| 0.5966        | 0.31  | 600  | 0.5963          | -0.2993        | -1.6491          | 0.7812             | 1.3499          | -273.4614      | -257.2279    | -2.8778         | -2.8986       |
-| 0.5014        | 0.36  | 700  | 0.5382          | -0.2859        | -1.4750          | 0.75               | 1.1891          | -271.7204      | -257.0942    | -2.7659         | -2.7869       |
-| 0.5334        | 0.41  | 800  | 0.5677          | -0.4289        | -1.8968          | 0.7969             | 1.4679          | -275.9378      | -258.5242    | -2.7053         | -2.7265       |
-| 0.5251        | 0.46  | 900  | 0.5772          | -0.2116        | -1.3107          | 0.7344             | 1.0991          | -270.0768      | -256.3507    | -2.8463         | -2.8662       |
-| 0.5205        | 0.52  | 1000 | 0.5262          | -0.3792        | -1.8585          | 0.7188             | 1.4793          | -275.5552      | -258.0276    | -2.7893         | -2.7979       |
-| 0.5094        | 0.57  | 1100 | 0.5433          | -0.6279        | -1.9368          | 0.7969             | 1.3089          | -276.3377      | -260.5136    | -2.7453         | -2.7536       |
-| 0.5837        | 0.62  | 1200 | 0.5349          | -0.3780        | -1.9584          | 0.7656             | 1.5804          | -276.5542      | -258.0154    | -2.7643         | -2.7756       |
-| 0.5214        | 0.67  | 1300 | 0.5732          | -1.0055        | -2.2306          | 0.7656             | 1.2251          | -279.2761      | -264.2903    | -2.6986         | -2.7113       |
-| 0.6914        | 0.72  | 1400 | 0.5137          | -0.6912        | -2.1775          | 0.7969             | 1.4863          | -278.7448      | -261.1467    | -2.7166         | -2.7275       |
-| 0.4655        | 0.77  | 1500 | 0.5090          | -0.7987        | -2.2930          | 0.7031             | 1.4943          | -279.8999      | -262.2220    | -2.6651         | -2.6838       |
-| 0.5731        | 0.83  | 1600 | 0.5312          | -0.8253        | -2.3520          | 0.7812             | 1.5268          | -280.4902      | -262.4876    | -2.6543         | -2.6728       |
-| 0.5233        | 0.88  | 1700 | 0.5206          | -0.4573        | -2.0951          | 0.7812             | 1.6377          | -277.9205      | -258.8084    | -2.6870         | -2.7097       |
-| 0.5593        | 0.93  | 1800 | 0.5231          | -0.5508        | -2.2000          | 0.7969             | 1.6492          | -278.9703      | -259.7433    | -2.6221         | -2.6519       |
-| 0.4967        | 0.98  | 1900 | 0.5290          | -0.5340        | -1.9570          | 0.8281             | 1.4230          | -276.5395      | -259.5749    | -2.6564         | -2.6878       |
-| 0.0921        | 1.03  | 2000 | 0.5368          | -1.1376        | -3.1615          | 0.7812             | 2.0239          | -288.5854      | -265.6111    | -2.6040         | -2.6345       |
-| 0.0733        | 1.08  | 2100 | 0.5453          | -1.1045        | -3.4451          | 0.7656             | 2.3406          | -291.4208      | -265.2799    | -2.6289         | -2.6595       |
-| 0.0972        | 1.14  | 2200 | 0.5571          | -1.6915        | -3.9823          | 0.8125             | 2.2908          | -296.7934      | -271.1505    | -2.6471         | -2.6709       |
-| 0.1058        | 1.19  | 2300 | 0.5789          | -1.0621        | -3.8941          | 0.7969             | 2.8319          | -295.9106      | -264.8563    | -2.5527         | -2.5798       |
-| 0.2423        | 1.24  | 2400 | 0.5455          | -1.1963        | -3.5590          | 0.7812             | 2.3627          | -292.5599      | -266.1981    | -2.5414         | -2.5784       |
-| 0.1177        | 1.29  | 2500 | 0.5889          | -1.8141        | -4.3942          | 0.7969             | 2.5801          | -300.9120      | -272.3761    | -2.4802         | -2.5189       |
-| 0.1213        | 1.34  | 2600 | 0.5683          | -1.4608        | -3.8420          | 0.8125             | 2.3812          | -295.3901      | -268.8436    | -2.4774         | -2.5207       |
-| 0.0889        | 1.39  | 2700 | 0.5890          | -1.6007        | -3.7337          | 0.7812             | 2.1330          | -294.3068      | -270.2423    | -2.4123         | -2.4522       |
-| 0.0995        | 1.45  | 2800 | 0.6073          | -1.5519        | -3.8362          | 0.8281             | 2.2843          | -295.3315      | -269.7538    | -2.4685         | -2.5050       |
-| 0.1145        | 1.5   | 2900 | 0.5790          | -1.7939        | -4.2876          | 0.8438             | 2.4937          | -299.8461      | -272.1744    | -2.4272         | -2.4674       |
-| 0.0644        | 1.55  | 3000 | 0.5735          | -1.7285        | -4.2051          | 0.8125             | 2.4766          | -299.0209      | -271.5201    | -2.4193         | -2.4574       |
-| 0.0798        | 1.6   | 3100 | 0.5537          | -1.7226        | -4.2850          | 0.8438             | 2.5624          | -299.8200      | -271.4610    | -2.5367         | -2.5696       |
-| 0.1013        | 1.65  | 3200 | 0.5575          | -1.5715        | -3.9813          | 0.875              | 2.4098          | -296.7825      | -269.9498    | -2.4926         | -2.5267       |
-| 0.1254        | 1.7   | 3300 | 0.5905          | -1.6412        | -4.4703          | 0.8594             | 2.8291          | -301.6730      | -270.6473    | -2.5017         | -2.5340       |
-| 0.085         | 1.76  | 3400 | 0.6133          | -1.9159        | -4.6760          | 0.8438             | 2.7601          | -303.7296      | -273.3941    | -2.4614         | -2.4960       |
-| 0.065         | 1.81  | 3500 | 0.6074          | -1.8237        | -4.3525          | 0.8594             | 2.5288          | -300.4951      | -272.4724    | -2.4597         | -2.5004       |
-| 0.0755        | 1.86  | 3600 | 0.5836          | -1.9252        | -4.4005          | 0.8125             | 2.4753          | -300.9748      | -273.4872    | -2.4327         | -2.4716       |
-| 0.0746        | 1.91  | 3700 | 0.5789          | -1.9280        | -4.4906          | 0.8125             | 2.5626          | -301.8762      | -273.5149    | -2.4686         | -2.5115       |
-| 0.1348        | 1.96  | 3800 | 0.6015          | -1.8658        | -4.2428          | 0.8281             | 2.3769          | -299.3976      | -272.8936    | -2.4943         | -2.5393       |
-| 0.0217        | 2.01  | 3900 | 0.6122          | -2.3335        | -4.9229          | 0.8281             | 2.5894          | -306.1988      | -277.5699    | -2.4841         | -2.5272       |
-| 0.0219        | 2.07  | 4000 | 0.6522          | -2.9890        | -6.0164          | 0.8281             | 3.0274          | -317.1334      | -284.1248    | -2.4105         | -2.4545       |
-| 0.0119        | 2.12  | 4100 | 0.6922          | -3.4777        | -6.6749          | 0.7969             | 3.1972          | -323.7187      | -289.0121    | -2.4272         | -2.4699       |
-| 0.0153        | 2.17  | 4200 | 0.6993          | -3.2406        | -6.6775          | 0.7969             | 3.4369          | -323.7453      | -286.6413    | -2.4047         | -2.4465       |
-| 0.011         | 2.22  | 4300 | 0.7178          | -3.7991        | -7.4397          | 0.7656             | 3.6406          | -331.3667      | -292.2260    | -2.3843         | -2.4290       |
-| 0.0072        | 2.27  | 4400 | 0.6840          | -3.3269        | -6.8021          | 0.8125             | 3.4752          | -324.9908      | -287.5042    | -2.4095         | -2.4536       |
-| 0.0197        | 2.32  | 4500 | 0.7013          | -3.6890        | -7.3014          | 0.8125             | 3.6124          | -329.9841      | -291.1250    | -2.4118         | -2.4543       |
-| 0.0182        | 2.37  | 4600 | 0.7476          | -3.8994        | -7.5366          | 0.8281             | 3.6372          | -332.3356      | -293.2291    | -2.4163         | -2.4565       |
-| 0.0125        | 2.43  | 4700 | 0.7199          | -4.0560        | -7.5765          | 0.8438             | 3.5204          | -332.7345      | -294.7952    | -2.3699         | -2.4100       |
-| 0.0082        | 2.48  | 4800 | 0.7048          | -3.6613        | -7.1356          | 0.875              | 3.4743          | -328.3255      | -290.8477    | -2.3925         | -2.4303       |
-| 0.0118        | 2.53  | 4900 | 0.6976          | -3.7908        | -7.3152          | 0.8125             | 3.5244          | -330.1224      | -292.1431    | -2.3633         | -2.4047       |
-| 0.0118        | 2.58  | 5000 | 0.7198          | -3.9049        | -7.5557          | 0.8281             | 3.6508          | -332.5271      | -293.2844    | -2.3764         | -2.4194       |
-| 0.006         | 2.63  | 5100 | 0.7506          | -4.2118        | -7.9149          | 0.8125             | 3.7032          | -336.1194      | -296.3530    | -2.3407         | -2.3860       |
-| 0.0143        | 2.68  | 5200 | 0.7408          | -4.2433        | -7.9802          | 0.8125             | 3.7369          | -336.7721      | -296.6682    | -2.3509         | -2.3946       |
-| 0.0057        | 2.74  | 5300 | 0.7552          | -4.3392        | -8.0831          | 0.7969             | 3.7439          | -337.8013      | -297.6275    | -2.3388         | -2.3842       |
-| 0.0138        | 2.79  | 5400 | 0.7404          | -4.2395        | -7.9762          | 0.8125             | 3.7367          | -336.7322      | -296.6304    | -2.3286         | -2.3737       |
-| 0.0079        | 2.84  | 5500 | 0.7525          | -4.4466        | -8.2196          | 0.7812             | 3.7731          | -339.1662      | -298.7007    | -2.3200         | -2.3641       |
-| 0.0077        | 2.89  | 5600 | 0.7520          | -4.5586        | -8.3485          | 0.7969             | 3.7899          | -340.4545      | -299.8206    | -2.3078         | -2.3517       |
-| 0.0094        | 2.94  | 5700 | 0.7527          | -4.5542        | -8.3509          | 0.7812             | 3.7967          | -340.4790      | -299.7773    | -2.3062         | -2.3510       |
-| 0.0054        | 2.99  | 5800 | 0.7520          | -4.5169        | -8.3079          | 0.7812             | 3.7911          | -340.0493      | -299.4038    | -2.3081         | -2.3530       |
 ### Framework versions
 - Transformers 4.35.0.dev0
@@ -427,18 +268,4 @@ If you use the UltraChat or UltraFeedback datasets, please cite the original wor
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
-```
-# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
-Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_HuggingFaceH4__zephyr-7b-beta)
-| Metric                | Value                     |
-|-----------------------|---------------------------|
-| Avg.                  | 52.15   |
-| ARC (25-shot)         | 62.03          |
-| HellaSwag (10-shot)   | 84.36    |
-| MMLU (5-shot)         | 61.07         |
-| TruthfulQA (0-shot)   | 57.45   |
-| Winogrande (5-shot)   | 77.74   |
-| GSM8K (5-shot)        | 12.74        |
-| DROP (3-shot)         | 9.66         |

       url: https://huggingface.co/spaces/lmsys/mt-bench
 ---
 ## Model description
 - **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
 - **License:** MIT
 - **Finetuned from model:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
 ## Intended uses & limitations
 Here's how you can run the model using the `pipeline()` function from 🤗 Transformers:
 ```python
 # Ah, me hearty matey! But yer question be a puzzler! A human cannot eat a helicopter in one sitting, as helicopters are not edible. They be made of metal, plastic, and other materials, not food!
 ```
 ### Framework versions
 - Transformers 4.35.0.dev0
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
+```