---
library_name: transformers
language:
- en
inference:
  parameters:
    max_new_tokens: 64
    do_sample: true
    temperature: 0.1
    repetition_penalty: 10
    no_repeat_ngram_size: 4
    eta_cutoff: 0.0006
    renormalize_logits: true
widget:
  - text: My name is El Microondas the Wise, and
    example_title: El Microondas
  - text: Kennesaw State University is a public
    example_title: Kennesaw State University
  - text: >-
      Bungie Studios is an American video game developer. They are most famous
      for developing the award winning Halo series of video games. They also
      made Destiny. The studio was founded
    example_title: Bungie
  - text: The Mona Lisa is a world-renowned painting created by
    example_title: Mona Lisa
  - text: >-
      The Harry Potter series, written by J.K. Rowling, begins with the book
      titled
    example_title: Harry Potter Series
  - text: >-
      Question: I have cities, but no houses. I have mountains, but no trees. I
      have water, but no fish. What am I?

      Answer:
    example_title: Riddle
  - text: The process of photosynthesis involves the conversion of
    example_title: Photosynthesis
  - text: >-
      Jane went to the store to buy some groceries. She picked up apples,
      oranges, and a loaf of bread. When she got home, she realized she forgot
    example_title: Story Continuation
  - text: >-
      Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
      and another train leaves Station B at 10:00 AM and travels at 80 mph, when
      will they meet if the distance between the stations is 300 miles?

      To determine
    example_title: Math Problem
  - text: In the context of computer programming, an algorithm is
    example_title: Algorithm Definition
pipeline_tag: text-generation
---


# Model Card for nano-phi-115M-v0.1

Inspired by [Phi2](https://huggingface.co/microsoft/phi-2), and open source small language model attempts like [smol_llama-101M-GQA](https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA).  
Pre-trained with training 7B token from scratch, with application of quality filter to datasets resulting in 0.26B token.  
The control is [kenhktsui/nano-phi-115M-control-v0.1](https://huggingface.co/kenhktsui/nano-phi-115M-control-v0.1), where full dataset (0.6B) is used.
Not much degradation in performance despite only using 42% of the data.
It just took 2d 4h to train in Colab with a A100 40GB (~USD$ 100).  
It achieves quite competitive results in evaluation given its training token, and training data size.  
Yet, there are still large gaps (particularly in ARC, HellaSwag, MMLU and GSM8K) between nano-phi-115M-v0.1 and phi-2, where author will attempt to narrow down the gap in the future.
No alignment has been done yet.  

## Some metrics
- model
  - hidden_size: 768
  - num_key_value_heads: 8 (grouped query attention)
  - num_attention_heads: 24
  - num_hidden_layers: 6
  - context length: 1024
  - total params: 115M
- training:
  - global steps: 14,000



## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

| Metric                | kenhktsui/nano-phi-115M-v0.1|[kenhktsui/nano-phi-115M-control-v0.1](https://huggingface.co/kenhktsui/nano-phi-115M-control-v0.1)|[microsoft/phi-2](https://huggingface.co/microsoft/phi-2)|
|-----------------------|---------------------------|---------------------------|---------------------------|
| Model Para            | 115M     |115M  |2.7B |
| Dataset Size          | 0.26B     |0.6B  |250B |
| Training Token        | 0.26B     |0.6B  |1.4T |
| Context Length        |1024      |1024  |2048|
| Device                |1xA100-40G|1xA100-40G |96xA100-80G|
| Training Time         |2d4h      |2d4h  |14d|


| Metric                | kenhktsui/nano-phi-115M-v0.1|[kenhktsui/nano-phi-115M-control-v0.1](https://huggingface.co/kenhktsui/nano-phi-115M-control-v0.1)|[microsoft/phi-2](https://huggingface.co/microsoft/phi-2) (Reproduced)|
|-----------------------|---------------------------|---------------------------|---------------------------|
| Avg.                  | 28.68    |28.75 |61.53 |
| ARC (25-shot)         | 21.93    |21.67 |61.52 |
| HellaSwag (10-shot)   | 27.87    |26.89 |75.13 |
| MMLU (5-shot)         | 25.30    |24.76 |58.23 |
| TruthfulQA (0-shot)   | 46.01    |47.69 |44.46 |
| Winogrande (5-shot)   | 50.99    |51.46 |74.51 |
| GSM8K (5-shot)        |  0.0     |0.0 |55.34  |

Details:

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16
|  Task  |Version| Metric |Value |   |Stderr|
|--------|------:|--------|-----:|---|-----:|
|arc_easy|      0|acc     |0.4263|±  |0.0101|
|        |       |acc_norm|0.3864|±  |0.0100|

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 25, batch_size: 16
|    Task     |Version| Metric |Value |   |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|arc_challenge|      0|acc     |0.1826|±  |0.0113|
|             |       |acc_norm|0.2193|±  |0.0121|

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 10, batch_size: 16
|  Task   |Version| Metric |Value |   |Stderr|
|---------|------:|--------|-----:|---|-----:|
|hellaswag|      0|acc     |0.2733|±  |0.0044|
|         |       |acc_norm|0.2787|±  |0.0045|

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16
|    Task     |Version|Metric|Value |   |Stderr|
|-------------|------:|------|-----:|---|-----:|
|truthfulqa_mc|      1|mc1   |0.2521|±  |0.0152|
|             |       |mc2   |0.4601|±  |0.0154|

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 5, batch_size: 16
|                      Task                       |Version| Metric |Value |   |Stderr|
|-------------------------------------------------|------:|--------|-----:|---|-----:|
|hendrycksTest-abstract_algebra                   |      1|acc     |0.2300|±  |0.0423|
|                                                 |       |acc_norm|0.2300|±  |0.0423|
|hendrycksTest-anatomy                            |      1|acc     |0.3111|±  |0.0400|
|                                                 |       |acc_norm|0.3111|±  |0.0400|
|hendrycksTest-astronomy                          |      1|acc     |0.2171|±  |0.0336|
|                                                 |       |acc_norm|0.2171|±  |0.0336|
|hendrycksTest-business_ethics                    |      1|acc     |0.2500|±  |0.0435|
|                                                 |       |acc_norm|0.2500|±  |0.0435|
|hendrycksTest-clinical_knowledge                 |      1|acc     |0.2226|±  |0.0256|
|                                                 |       |acc_norm|0.2226|±  |0.0256|
|hendrycksTest-college_biology                    |      1|acc     |0.2292|±  |0.0351|
|                                                 |       |acc_norm|0.2292|±  |0.0351|
|hendrycksTest-college_chemistry                  |      1|acc     |0.1700|±  |0.0378|
|                                                 |       |acc_norm|0.1700|±  |0.0378|
|hendrycksTest-college_computer_science           |      1|acc     |0.2500|±  |0.0435|
|                                                 |       |acc_norm|0.2500|±  |0.0435|
|hendrycksTest-college_mathematics                |      1|acc     |0.2500|±  |0.0435|
|                                                 |       |acc_norm|0.2500|±  |0.0435|
|hendrycksTest-college_medicine                   |      1|acc     |0.2023|±  |0.0306|
|                                                 |       |acc_norm|0.2023|±  |0.0306|
|hendrycksTest-college_physics                    |      1|acc     |0.3235|±  |0.0466|
|                                                 |       |acc_norm|0.3235|±  |0.0466|
|hendrycksTest-computer_security                  |      1|acc     |0.2600|±  |0.0441|
|                                                 |       |acc_norm|0.2600|±  |0.0441|
|hendrycksTest-conceptual_physics                 |      1|acc     |0.2511|±  |0.0283|
|                                                 |       |acc_norm|0.2511|±  |0.0283|
|hendrycksTest-econometrics                       |      1|acc     |0.2281|±  |0.0395|
|                                                 |       |acc_norm|0.2281|±  |0.0395|
|hendrycksTest-electrical_engineering             |      1|acc     |0.2276|±  |0.0349|
|                                                 |       |acc_norm|0.2276|±  |0.0349|
|hendrycksTest-elementary_mathematics             |      1|acc     |0.2460|±  |0.0222|
|                                                 |       |acc_norm|0.2460|±  |0.0222|
|hendrycksTest-formal_logic                       |      1|acc     |0.1508|±  |0.0320|
|                                                 |       |acc_norm|0.1508|±  |0.0320|
|hendrycksTest-global_facts                       |      1|acc     |0.3000|±  |0.0461|
|                                                 |       |acc_norm|0.3000|±  |0.0461|
|hendrycksTest-high_school_biology                |      1|acc     |0.3387|±  |0.0269|
|                                                 |       |acc_norm|0.3387|±  |0.0269|
|hendrycksTest-high_school_chemistry              |      1|acc     |0.2906|±  |0.0319|
|                                                 |       |acc_norm|0.2906|±  |0.0319|
|hendrycksTest-high_school_computer_science       |      1|acc     |0.3100|±  |0.0465|
|                                                 |       |acc_norm|0.3100|±  |0.0465|
|hendrycksTest-high_school_european_history       |      1|acc     |0.2182|±  |0.0323|
|                                                 |       |acc_norm|0.2182|±  |0.0323|
|hendrycksTest-high_school_geography              |      1|acc     |0.3232|±  |0.0333|
|                                                 |       |acc_norm|0.3232|±  |0.0333|
|hendrycksTest-high_school_government_and_politics|      1|acc     |0.2021|±  |0.0290|
|                                                 |       |acc_norm|0.2021|±  |0.0290|
|hendrycksTest-high_school_macroeconomics         |      1|acc     |0.2487|±  |0.0219|
|                                                 |       |acc_norm|0.2487|±  |0.0219|
|hendrycksTest-high_school_mathematics            |      1|acc     |0.2741|±  |0.0272|
|                                                 |       |acc_norm|0.2741|±  |0.0272|
|hendrycksTest-high_school_microeconomics         |      1|acc     |0.3319|±  |0.0306|
|                                                 |       |acc_norm|0.3319|±  |0.0306|
|hendrycksTest-high_school_physics                |      1|acc     |0.3179|±  |0.0380|
|                                                 |       |acc_norm|0.3179|±  |0.0380|
|hendrycksTest-high_school_psychology             |      1|acc     |0.2477|±  |0.0185|
|                                                 |       |acc_norm|0.2477|±  |0.0185|
|hendrycksTest-high_school_statistics             |      1|acc     |0.4722|±  |0.0340|
|                                                 |       |acc_norm|0.4722|±  |0.0340|
|hendrycksTest-high_school_us_history             |      1|acc     |0.2696|±  |0.0311|
|                                                 |       |acc_norm|0.2696|±  |0.0311|
|hendrycksTest-high_school_world_history          |      1|acc     |0.2152|±  |0.0268|
|                                                 |       |acc_norm|0.2152|±  |0.0268|
|hendrycksTest-human_aging                        |      1|acc     |0.1973|±  |0.0267|
|                                                 |       |acc_norm|0.1973|±  |0.0267|
|hendrycksTest-human_sexuality                    |      1|acc     |0.2824|±  |0.0395|
|                                                 |       |acc_norm|0.2824|±  |0.0395|
|hendrycksTest-international_law                  |      1|acc     |0.2231|±  |0.0380|
|                                                 |       |acc_norm|0.2231|±  |0.0380|
|hendrycksTest-jurisprudence                      |      1|acc     |0.2222|±  |0.0402|
|                                                 |       |acc_norm|0.2222|±  |0.0402|
|hendrycksTest-logical_fallacies                  |      1|acc     |0.2822|±  |0.0354|
|                                                 |       |acc_norm|0.2822|±  |0.0354|
|hendrycksTest-machine_learning                   |      1|acc     |0.2768|±  |0.0425|
|                                                 |       |acc_norm|0.2768|±  |0.0425|
|hendrycksTest-management                         |      1|acc     |0.2039|±  |0.0399|
|                                                 |       |acc_norm|0.2039|±  |0.0399|
|hendrycksTest-marketing                          |      1|acc     |0.1966|±  |0.0260|
|                                                 |       |acc_norm|0.1966|±  |0.0260|
|hendrycksTest-medical_genetics                   |      1|acc     |0.2800|±  |0.0451|
|                                                 |       |acc_norm|0.2800|±  |0.0451|
|hendrycksTest-miscellaneous                      |      1|acc     |0.2746|±  |0.0160|
|                                                 |       |acc_norm|0.2746|±  |0.0160|
|hendrycksTest-moral_disputes                     |      1|acc     |0.2081|±  |0.0219|
|                                                 |       |acc_norm|0.2081|±  |0.0219|
|hendrycksTest-moral_scenarios                    |      1|acc     |0.2469|±  |0.0144|
|                                                 |       |acc_norm|0.2469|±  |0.0144|
|hendrycksTest-nutrition                          |      1|acc     |0.2647|±  |0.0253|
|                                                 |       |acc_norm|0.2647|±  |0.0253|
|hendrycksTest-philosophy                         |      1|acc     |0.1897|±  |0.0223|
|                                                 |       |acc_norm|0.1897|±  |0.0223|
|hendrycksTest-prehistory                         |      1|acc     |0.2377|±  |0.0237|
|                                                 |       |acc_norm|0.2377|±  |0.0237|
|hendrycksTest-professional_accounting            |      1|acc     |0.2482|±  |0.0258|
|                                                 |       |acc_norm|0.2482|±  |0.0258|
|hendrycksTest-professional_law                   |      1|acc     |0.2464|±  |0.0110|
|                                                 |       |acc_norm|0.2464|±  |0.0110|
|hendrycksTest-professional_medicine              |      1|acc     |0.4265|±  |0.0300|
|                                                 |       |acc_norm|0.4265|±  |0.0300|
|hendrycksTest-professional_psychology            |      1|acc     |0.2614|±  |0.0178|
|                                                 |       |acc_norm|0.2614|±  |0.0178|
|hendrycksTest-public_relations                   |      1|acc     |0.1818|±  |0.0369|
|                                                 |       |acc_norm|0.1818|±  |0.0369|
|hendrycksTest-security_studies                   |      1|acc     |0.1959|±  |0.0254|
|                                                 |       |acc_norm|0.1959|±  |0.0254|
|hendrycksTest-sociology                          |      1|acc     |0.2289|±  |0.0297|
|                                                 |       |acc_norm|0.2289|±  |0.0297|
|hendrycksTest-us_foreign_policy                  |      1|acc     |0.2400|±  |0.0429|
|                                                 |       |acc_norm|0.2400|±  |0.0429|
|hendrycksTest-virology                           |      1|acc     |0.2048|±  |0.0314|
|                                                 |       |acc_norm|0.2048|±  |0.0314|
|hendrycksTest-world_religions                    |      1|acc     |0.2222|±  |0.0319|
|                                                 |       |acc_norm|0.2222|±  |0.0319|

hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 5, batch_size: 16
|   Task   |Version|Metric|Value |   |Stderr|
|----------|------:|------|-----:|---|-----:|
|winogrande|      0|acc   |0.5099|±  | 0.014|


hf-causal-experimental (pretrained=/content/lm-evaluation-harness/artifacts/checkpoint-pegfss6f:v13,use_accelerate=false,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 5, batch_size: 16
|   Task   |Version|Metric|Value |   |Stderr|
|----------|------:|------|-----:|---|-----:|
|gsm8k     |      0|acc   |   0.0|±  |   0.0|



## Model Details

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