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--- |
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license: mit |
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language: |
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- en |
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- de |
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- es |
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- nl |
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- fr |
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--- |
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# Multilingual e-SNLI (MLe-SNLI) |
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In this repo, we provide the training, validation, and testing sets for **M**ulti**l**ingual **e-SNLI** (MLe-SNLI). For more details, find our report [here](https://github.com/rish-16/cs4248-project/blob/main/CS4248_Group19_Final_Report.pdf). |
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## Dataset details |
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MLe-SNLI contains 500K training (`train`) samples of premise-hypothesis pairs along with their associated label and explanation. We take 100K training samples from the original e-SNLI (Camburu et al., 2018) dataset and translate them into 4 other languages (Spanish, German, Dutch, and French). We do the same for all 9824 testing (`test`) and validation (`dev`) samples, giving us 49120 samples for both `test` and `dev` splits. |
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| Column | Description | |
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|-----------------|---------------------------------------------------------------------------------| |
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| `premise` | Natural language premise sentence | |
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| `hypothesis` | Natural language hypothesis sentence | |
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| `label` | From `entailment`, `contradiction`, or `neutral` | |
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| `explanation_1` | Natural language justification for `label` | |
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| `language` | From English (`en`), Spanish (`es`), German (`de`), Dutch (`nl`), French (`fr`) | |
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> **WARNING:** the translation quality of MLe-SNLI may be compromised for some natural language samples because of quality issues in the original e-SNLI dataset that were not addressed in our [work](https://github.com/rish-16/cs4248-project). Use it at your own discretion. |
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## Download Instructions |
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To access MLe-SNLI, you can use the HuggingFace Datasets API to load the dataset: |
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```python |
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from datasets import load_dataset |
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mle_snli = load_dataset("rish16/MLe-SNLI") # loads a DatasetDict object |
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train_data = mle_snli['train'] # 500K samples (100K per lang) |
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dev_data = mle_snli['dev'] # 49120 samples (9824 per lang) |
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test_data = mle_snli['test'] # 49120 samples (9824 per lang) |
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print (mle_snli) |
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""" |
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DatasetDict({ |
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train: Dataset({ |
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features: ['premise', 'hypothesis', 'label', 'explanation_1', 'language'], |
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num_rows: 500000 |
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}) |
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test: Dataset({ |
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features: ['premise', 'hypothesis', 'label', 'explanation_1', 'language'], |
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num_rows: 49120 |
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}) |
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validation: Dataset({ |
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features: ['premise', 'hypothesis', 'label', 'explanation_1', 'language'], |
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num_rows: 49210 |
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}) |
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}) |
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""" |
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``` |
