---
tags:
- generated_from_trainer
metrics:
- accuracy
inference:
  parameters:
    max_new_tokens: 64
    do_sample: true
    repetition_penalty: 1.1
    no_repeat_ngram_size: 5
    guidance_scale: 1.01
    eta_cutoff: 0.001
widget:
  - text: My name is El Microondas the Wise and
    example_title: El Microondas
  - text: A meme is
    example_title: meme
  - text: >-
      Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
      He chose her because she had
    example_title: Coreference resolution
  - text: >-
      On a shelf, there are five books: a gray book, a red book, a purple book,
      a blue book, and a black book
    example_title: Logic puzzles
  - text: >-
      The two men running to become New York City's next mayor will face off in
      their first debate Wednesday night
    example_title: Reading comprehension
pipeline_tag: text-generation
license: apache-2.0
language:
  - en
---

# pythia-31m-KI_v1-2048-scratch

Initialized from random weights based on config of [EleutherAI/pythia-31m](https://huggingface.co/EleutherAI/pythia-31m), 3 epochs bf16
It achieves the following results on the evaluation set:
- Loss: 4.6160
- Accuracy: 0.2448

## 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 80085
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.3874        | 0.16  | 100  | 6.4212          | 0.1487   |
| 5.7088        | 0.32  | 200  | 5.7926          | 0.1725   |
| 5.4575        | 0.48  | 300  | 5.5160          | 0.1903   |
| 5.2451        | 0.64  | 400  | 5.3429          | 0.1995   |
| 5.0954        | 0.8   | 500  | 5.2109          | 0.2059   |
| 5.0358        | 0.96  | 600  | 5.1068          | 0.2123   |
| 4.94          | 1.12  | 700  | 5.0321          | 0.2157   |
| 4.8532        | 1.28  | 800  | 4.9605          | 0.2202   |
| 4.7602        | 1.44  | 900  | 4.9047          | 0.224    |
| 4.6965        | 1.6   | 1000 | 4.8526          | 0.2276   |
| 4.6855        | 1.76  | 1100 | 4.8139          | 0.2300   |
| 4.6573        | 1.91  | 1200 | 4.7739          | 0.2327   |
| 4.5968        | 2.07  | 1300 | 4.7451          | 0.2346   |
| 4.5688        | 2.23  | 1400 | 4.7152          | 0.2370   |
| 4.5205        | 2.39  | 1500 | 4.6842          | 0.2396   |
| 4.5369        | 2.55  | 1600 | 4.6598          | 0.2410   |
| 4.5106        | 2.71  | 1700 | 4.6352          | 0.2433   |
| 4.4375        | 2.87  | 1800 | 4.6160          | 0.2448   |


# [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_pszemraj__pythia-31m-KI_v1-2048-scratch)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 25.21   |
| ARC (25-shot)         | 23.12          |
| HellaSwag (10-shot)   | 25.23    |
| MMLU (5-shot)         | 23.12         |
| TruthfulQA (0-shot)   | 51.67   |
| Winogrande (5-shot)   | 51.78   |
| GSM8K (5-shot)        | 0.0        |
| DROP (3-shot)         | 1.52         |