metadata
base_model: roneneldan/TinyStories-33M
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
datasets:
- pszemraj/simple_wikipedia_LM
license: apache-2.0
language:
- en
GPT-Neo-33M-simplewiki-2048-scratch
Initialized from random weights based on config from roneneldan/TinyStories-33M, 3 epochs bf16.
It achieves the following results on the evaluation set:
- Loss: 3.9511
- Accuracy: 0.3843
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 |
|---|---|---|---|---|
| 5.4676 | 0.45 | 100 | 5.0139 | 0.2811 |
| 5.1729 | 0.89 | 200 | 4.6737 | 0.3050 |
| 4.8702 | 1.34 | 300 | 4.4922 | 0.3170 |
| 4.5538 | 1.79 | 400 | 4.3026 | 0.3348 |
| 4.4818 | 2.23 | 500 | 4.0908 | 0.3649 |
| 4.4583 | 2.68 | 600 | 3.9511 | 0.3843 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230907+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3