README.md

---
license: apache-2.0
tags:
- recsys
- retrieval
- dataset
pretty_name: Yambda-5B
size_categories:
- 1B<n<10B

configs:
- config_name: flat-50m
  data_files:
    - split: likes
      path: flat/50m/likes.parquet
    - split: listens
      path: flat/50m/listens.parquet
    - split: unlikes
      path: flat/50m/unlikes.parquet
    - split: multi_event
      path: flat/50m/multi_event.parquet
    - split: dislikes
      path: flat/50m/dislikes.parquet
    - split: undislikes
      path: flat/50m/undislikes.parquet
- config_name: flat-500m
  data_files:
    - split: likes
      path: flat/500m/likes.parquet
    - split: listens
      path: flat/500m/listens.parquet
    - split: unlikes
      path: flat/500m/unlikes.parquet
    - split: multi_event
      path: flat/500m/multi_event.parquet
    - split: dislikes
      path: flat/500m/dislikes.parquet
    - split: undislikes
      path: flat/500m/undislikes.parquet
- config_name: flat-5b
  data_files:
    - split: likes
      path: flat/5b/likes.parquet
    - split: listens
      path: flat/5b/listens.parquet
    - split: unlikes
      path: flat/5b/unlikes.parquet
    - split: multi_event
      path: flat/5b/multi_event.parquet
    - split: dislikes
      path: flat/5b/dislikes.parquet
    - split: undislikes
      path: flat/5b/undislikes.parquet
- config_name: sequential-50m
  data_files:
    - split: likes
      path: sequential/50m/likes.parquet
    - split: listens
      path: sequential/50m/listens.parquet
    - split: unlikes
      path: sequential/50m/unlikes.parquet
    - split: multi_event
      path: sequential/50m/multi_event.parquet
    - split: dislikes
      path: sequential/50m/dislikes.parquet
    - split: undislikes
      path: sequential/50m/undislikes.parquet
- config_name: sequential-500m
  data_files:
    - split: likes
      path: sequential/500m/likes.parquet
    - split: listens
      path: sequential/500m/listens.parquet
    - split: unlikes
      path: sequential/500m/unlikes.parquet
    - split: multi_event
      path: sequential/500m/multi_event.parquet
    - split: dislikes
      path: sequential/500m/dislikes.parquet
    - split: undislikes
      path: sequential/500m/undislikes.parquet
- config_name: sequential-5b
  data_files:
    - split: likes
      path: sequential/5b/likes.parquet
    - split: listens
      path: sequential/5b/listens.parquet
    - split: unlikes
      path: sequential/5b/unlikes.parquet
    - split: multi_event
      path: sequential/5b/multi_event.parquet
    - split: dislikes
      path: sequential/5b/dislikes.parquet
    - split: undislikes
      path: sequential/5b/undislikes.parquet

---

# Yambda-5B — A Large-Scale Multi-modal Dataset for Ranking And Retrieval

**Industrial-scale music recommendation dataset with organic/recommendation interactions and audio embeddings**

 [📌 Overview](#overview) • [🔑 Key Features](#key-features) • [📊 Statistics](#statistics) • [📝 Format](#data-format) • [🏆 Benchmark](#benchmark) • [❓ FAQ](#faq)

## Overview

The Yambda-5B dataset is a large-scale open database comprising **4.79 billion user-item interactions** collected from **1 million users** and spanning **9.39 million tracks**. The dataset includes both implicit feedback, such as listening events, and explicit feedback, in the form of likes and dislikes. Additionally, it provides distinctive markers for organic versus recommendation-driven interactions, along with precomputed audio embeddings to facilitate content-aware recommendation systems.

## Key Features

- 🎵 4.79B user-music interactions (listens, likes, dislikes, unlikes, undislikes)
- 🕒 Timestamps with global temporal ordering
- 🔊 Audio embeddings for 7.72M tracks
- 💡 Organic and recommendation-driven interactions
- 📈 Multiple dataset scales (50M, 500M, 5B interactions)
- 🧪 Standardized evaluation protocol with baseline benchmarks

## About Dataset

### Statistics

| Dataset     |     Users |     Items |       Listens |      Likes |   Dislikes |
|-------------|----------:|----------:|--------------:|-----------:|-----------:|
| Yambda-50M  |    10,000 |   934,057 |    46,467,212 |    881,456 |    107,776 |
| Yambda-500M |   100,000 | 3,004,578 |   466,512,103 |  9,033,960 |  1,128,113 |
| Yambda-5B   | 1,000,000 | 9,390,623 | 4,649,567,411 | 89,334,605 | 11,579,143 |

### User History Length Distribution

![user history length](assets/img/user_history_len.png "User History Length")

![user history length log-scale](assets/img/user_history_log_len.png "User History Length Log-scale")

### Item Interaction Count

![item interaction count log-scale](assets/img/item_interactions.png "Item Interaction Count Log-scale")

## Data Format

### File Descriptions

| File                       | Description                                 | Schema                                                                                  |
|----------------------------|---------------------------------------------|-----------------------------------------------------------------------------------------|
| `listens.parquet`          | User listening events with playback details | `uid`, `item_id`, `timestamp`, `is_organic`, `played_ratio_pct`, `track_length_seconds` |
| `likes.parquet`            | User like actions                           | `uid`, `item_id`, `timestamp`, `is_organic`                                             |
| `dislikes.parquet`         | User dislike actions                        | `uid`, `item_id`, `timestamp`, `is_organic`                                             |
| `undislikes.parquet`       | User undislike actions (reverting dislikes) | `uid`, `item_id`, `timestamp`, `is_organic`                                             |
| `unlikes.parquet`          | User unlike actions (reverting likes)       | `uid`, `item_id`, `timestamp`, `is_organic`                                             |
| `embeddings.parquet`       | Track audio-embeddings                      | `item_id`, `embed`, `normalized_embed`                                                  |

### Common Event Structure (Homogeneous)

Most event files (`listens`, `likes`, `dislikes`, `undislikes`, `unlikes`) share this base structure:

| Field        | Type   | Description                                                                         |
|--------------|--------|-------------------------------------------------------------------------------------|
| `uid`        | uint32 | Unique user identifier                                                              |
| `item_id`    | uint32 | Unique track identifier                                                             |
| `timestamp`  | uint32 | Delta times, binned into 5s units.                                                  |
| `is_organic` | uint8  | Boolean flag (0/1) indicating if the interaction was algorithmic (0) or organic (1) |

**Sorting**: All files are sorted by (`uid`, `timestamp`) in ascending order.

### Unified Event Structure (Heterogeneous)

For applications needing all event types in a unified format:

| Field                  | Type              | Description                                                   |
|------------------------|-------------------|---------------------------------------------------------------|
| `uid`                  | uint32            | Unique user identifier                                        |
| `item_id`              | uint32            | Unique track identifier                                       |
| `timestamp`            | uint32            | Timestamp binned into 5s units.granularity                    |
| `is_organic`           | uint8             | Boolean flag for organic interactions                         |
| `event_type`           | enum              | One of: `listen`, `like`, `dislike`, `unlike`, `undislike`    |
| `played_ratio_pct`     | Optional[uint16] | Percentage of track played (1-100), null for non-listen events |
| `track_length_seconds` | Optional[uint32] | Total track duration in seconds, null for non-listen events    |

**Notes**:

- `played_ratio_pct` and `track_length_seconds` are non-null **only** when `event_type = "listen"`
- All fields except the two above are guaranteed non-null

### Sequential (Aggregated) Format

Each dataset is also available in a user-aggregated sequential format with the following structure:

| Field        | Type         | Description                                      |
|--------------|--------------|--------------------------------------------------|
| `uid`        | uint32       | Unique user identifier                           |
| `item_ids`   | List[uint32] | Chronological list of interacted track IDs       |
| `timestamps` | List[uint32] | Corresponding interaction timestamps             |
| `is_organic` | List[uint8]  | Corresponding organic flags for each interaction |
| `played_ratio_pct`     | List[Optional[uint16]] | (Only in `listens` and `multi_event`) Play percentages |
| `track_length_seconds` | List[Optional[uint32]] | (Only in `listens` and `multi_event`) Track durations  |

**Notes**:

- All lists maintain chronological order
- For each user, `len(item_ids) == len(timestamps) == len(is_organic)`
- In multi-event format, null values are preserved in respective lists

## Benchmark

Code for the baseline models can be found in `benchmarks/` directory, see [Reproducibility Guide](benchmarks/models/README.md)

## FAQ

### Are test items presented in training data?

Not all, some test items do appear in the training set, others do not.

### Are test users presented in training data?

Yes, there are no cold users in the test set.

### How are audio embeddings generated?

Using a convolutional neural network inspired by [J. Spijkervet et al., 2021](https://arxiv.org/abs/2103.09410).

### What's the `is_organic` flag?

Indicates whether interactions occurred through organic discovery (True) or recommendation-driven pathways (False)

### Which events are considered recommendation-driven?

Recommendation events include actions from:
- Personalized music feed
- Personalized playlists

### What counts as a "listened" track or \\(Listen_+\\)?

A track is considered "listened" if over 50% of its duration is played.