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---
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 |
|