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  1. README.md +34 -243
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@@ -17,9 +17,9 @@ language:
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  - rus
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  license: unknown
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  multilinguality: translated
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- task_ids: []
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  task_categories:
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  - text-classification
 
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  tags:
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  - mteb
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  - text
@@ -28,255 +28,28 @@ domains:
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  - Fiction
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  - Government
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  - Written
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  ---
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  <!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
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- # XNLIV2
 
 
 
 
 
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  This is subset of 'XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding' with languages that were not part of the original XNLI plus three (verified) languages that are not strongly covered in MTEB
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- > This dataset is included as a task in [`mteb`](https://github.com/embeddings-benchmark/mteb).
 
 
 
 
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- - Task category: t2t
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- - Domains: ['Non-fiction', 'Fiction', 'Government', 'Written']
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  ## How to evaluate on this task
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  ```python
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  import mteb
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@@ -288,7 +61,7 @@ evaluator.run(model)
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  ```
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  <!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
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- Reference: https://arxiv.org/pdf/2301.06527
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  ## Citation
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@@ -327,6 +100,19 @@ If you use this dataset, please cite the dataset as well as [mteb](https://githu
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  ```
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  # Dataset Statistics
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```json
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  {
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  "test": {
@@ -640,4 +426,9 @@ If you use this dataset, please cite the dataset as well as [mteb](https://githu
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  }
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  }
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  }
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- ```
 
 
 
 
 
 
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  - rus
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  license: unknown
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  multilinguality: translated
 
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  task_categories:
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  - text-classification
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+ task_ids: []
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  tags:
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  - mteb
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  - text
 
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  - Fiction
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  - Government
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  - Written
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
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+
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+ <div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">
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+ <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">XNLIV2</h1>
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+ <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">An <a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;" onmouseover="this.style.textDecoration='underline'" onmouseout="this.style.textDecoration='none'">MTEB</a> dataset</div>
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+ <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>
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+ </div>
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  This is subset of 'XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding' with languages that were not part of the original XNLI plus three (verified) languages that are not strongly covered in MTEB
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+ | | |
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+ |----------------|---------------------------------------------|
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+ | Task category: | t2t |
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+ | Domains | ['Non-fiction', 'Fiction', 'Government', 'Written'] |
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+ | Reference | https://arxiv.org/pdf/2301.06527 |
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  ## How to evaluate on this task
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+ You can evaluate an embedding model on this dataset using the following code:
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+
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  ```python
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  import mteb
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  ```
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  <!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
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+ To learn more about how to run models on `mteb` task check out the [GitHub repitory](https://github.com/embeddings-benchmark/mteb).
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  ## Citation
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  ```
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  # Dataset Statistics
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+ <details>
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+ <summary> Dataset Statistics</summary>
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+
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+ The following code contains the descriptive statistics from the task. These can also be obtained using:
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+
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+ ```python
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+ import mteb
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+
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+ task = mteb.get_task("XNLIV2")
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+
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+ desc_stats = task.metadata.descriptive_stats
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+ ```
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+
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  ```json
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  {
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  "test": {
 
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  }
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  }
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  }
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+ ```
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+
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+ </details>
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+
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+ ---
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+ *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*