The code for two papers: Feedback Transformer and Expire-Span.

Related tags

Deep Learningtransformer-sequential
Overview

transformer-sequential

This repo contains the code for two papers:

  • Feedback Transformer
  • Expire-Span

The training code is structured for long sequential modeling with Transformer-like architectures.

Requirements

You will need a CUDA-enabled GPU to run the code.

Setup

Run the following:

pip install -r requirements.txt

Feedback Transformer

Introduced in Addressing Some Limitations of Transformers with Feedback Memory.

Running Experiments from the Paper

enwik8

Model Params Valid Test
Feedback Transformer 77M 0.984 0.962

Numbers are Bits-Per-Character

bash experiments/feedback/enwik8.sh

Algorithmic

Model 3 Variable 5 Variable
Transformer 33.7 37.5
Feedback Transformer 99.1 92.6

Numbers are % Accuracy on Test

bash experiments/feedback/algorithmic_3var.sh
bash experiments/feedback/algorithmic_5var.sh

Expire-Span

Introduced in Not All Memories are Created Equal: Learning to Expire.

Running Experiments from the Paper

enwik8

Model Params Valid Test
Expire-Span 12L 38M 1.014 0.994

Numbers are Bits-Per-Character

bash experiments/expire_span/enwik8.sh

Object Collision

Model Maximum Span Test Error (%)
Expire-Span 16k 52.2
Expire-Span 32k 36.7
Expire-Span 64k 26.7 
bash experiments/expire_span/object_collision_16k.sh
bash experiments/expire_span/object_collision_32k.sh
bash experiments/expire_span/object_collision_64k.sh

License

The code is licensed under CC-BY-NC license. See the LICENSE file for more details.

Owner
Facebook Research
Facebook Research
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