|
--- |
|
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 | |
|
|
