metadata

license: apache-2.0
base_model: pszemraj/mega-ar-small-4096-NC-simplewiki-v1
tags:
  - generated_from_trainer
metrics:
  - accuracy
inference:
  parameters:
    max_new_tokens: 64
    do_sample: true
    repetition_penalty: 1.1
    no_repeat_ngram_size: 5
    eta_cutoff: 0.001
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
datasets:
  - JeanKaddour/minipile
  - pszemraj/simple_wikipedia_LM

mega-ar-small-4096-NC-minipile-v1

65M parameter MEGA autoregressive model initialized from scratch and trained on:

pszemraj/simple_wikipedia_LM
JeanKaddour/minipile

It achieves the following results on the evaluation set:

Loss: 3.7502
Accuracy: 0.3650

eval

initial 'get the feet wet':

hf-causal-experimental (pretrained=pszemraj/mega-ar-small-4096-sw_minipile,revision=main,trust_remote_code=True,dtype='float'), limit: None, provide_description: False, num_fewshot: 0, batch_size: 16

Task	Version	Metric	Value		Stderr
arc_easy	0	acc	0.3173	±	0.0096
		acc_norm	0.3022	±	0.0094
boolq	1	acc	0.4107	±	0.0086
lambada_openai	0	ppl	6843.1824	±	295.0792
		acc	0.0155	±	0.0017
openbookqa	0	acc	0.1220	±	0.0147
		acc_norm	0.2480	±	0.0193
piqa	0	acc	0.5609	±	0.0116
		acc_norm	0.5566	±	0.0116
winogrande	0	acc	0.5059	±	0.0141

still some ways to go.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0003
train_batch_size: 1
eval_batch_size: 1
seed: 80085
gradient_accumulation_steps: 64
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 1.0

Framework versions

Transformers 4.33.1
Pytorch 2.2.0.dev20230907+cu118
Datasets 2.14.5
Tokenizers 0.13.3