File size: 4,067 Bytes
90d65c3 3c645da c79abc3 3c645da bd53999 3c645da 502ee16 c79abc3 502ee16 3c645da ae15e66 3c645da 9904f80 3c645da 9904f80 3c645da 928e689 3c645da 8f6ee48 3c645da |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
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. -->
This model is a fine-tuned model for Chat based on [mosaicml/mpt-7b](https://huggingface.co/mosaicml/mpt-7b) with **max_seq_lenght=2048** on [databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k), [TigerResearch/tigerbot-alpaca-en-50k](https://huggingface.co/datasets/TigerResearch/tigerbot-alpaca-en-50k), [TigerResearch/tigerbot-gsm-8k-en](https://huggingface.co/datasets/TigerResearch/tigerbot-gsm-8k-en), [TigerResearch/tigerbot-alpaca-zh-0.5m](https://huggingface.co/datasets/TigerResearch/tigerbot-alpaca-zh-0.5m), [TigerResearch/tigerbot-stackexchange-qa-en-0.5m](https://huggingface.co/datasets/TigerResearch/tigerbot-stackexchange-qa-en-0.5m), [HC3](https://huggingface.co/datasets/Hello-SimpleAI/HC3) dataset.
## Model date
Neural-chat-7b-v1.1 was trained between June and July 2023.
## Evaluation
We use the same evaluation metrics as [open_llm_leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) which uses [Eleuther AI Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/master), a unified framework to test generative language models on a large number of different evaluation tasks.
| Model | Average ⬆️| ARC (25-s) ⬆️ | HellaSwag (10-s) ⬆️ | MMLU (5-s) ⬆️| TruthfulQA (MC) (0-s) ⬆️ |
| --- | --- | --- | --- | --- | --- |
|[mosaicml/mpt-7b](https://huggingface.co/mosaicml/mpt-7b)| 47.4 | 47.61 | 77.56 | 31 | 33.43 |
| [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat) | **49.95** | 46.5 | 75.55 | 37.60 | 40.17 |
| **Ours** | **51.41** | 50.09 | 76.69 | 38.79 | 40.07 |
### Bias evaluation
Following the blog [evaluating-llm-bias](https://huggingface.co/blog/evaluating-llm-bias), we select 10000 samples randomly from [allenai/real-toxicity-prompts](https://huggingface.co/datasets/allenai/real-toxicity-prompts) to evaluate toxicity bias in Language Models
| Model | Toxicity Rito ↓|
|[mosaicml/mpt-7b](https://huggingface.co/mosaicml/mpt-7b)| 0.027 |
| **Ours** | 0.0264 |
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 3.0
## Inference with transformers
```shell
import transformers
model = transformers.AutoModelForCausalLM.from_pretrained(
'Intel/neural-chat-7b-v1-1',
trust_remote_code=True
)
```
## Inference with INT8
Follow the instructions [link](https://github.com/intel/intel-extension-for-transformers/tree/main/examples/huggingface/pytorch/text-generation/quantization) to install the necessary dependencies. Use the below command to quantize the model using Intel Neural Compressor [link](https://github.com/intel/neural-compressor) and accelerate the inference.
```shell
python run_generation.py \
--model Intel/neural-chat-7b-v1-1 \
--quantize \
--sq \
--alpha 0.95 \
--ipex
```
### Examples
- code generation
- summarization
- trip
## Organizations developing the model
The NeuralChat team with members from Intel/SATG/AIA/AIPT. Core team members: Kaokao Lv, Liang Lv, Chang Wang, Wenxin Zhang, Xuhui Ren, and Haihao Shen.
## Useful links
* Intel Neural Compressor [link](https://github.com/intel/neural-compressor)
* Intel Extension for Transformers [link](https://github.com/intel/intel-extension-for-transformers)
* Intel Extension for PyTorch [link](https://github.com/intel/intel-extension-for-pytorch)
|