scoris/en-lt-merged-data

The data set is a merge of other open datasets:

• wmt19 (lt-en)
• opus100 (en-lt)
• sentence-transformers/parallel-sentences
  • Europarl-en-lt-train.tsv.gz
  • JW300-en-lt-train.tsv.gz
  • OpenSubtitles-en-lt-train.tsv.gz
  • Talks-en-lt-train.tsv.gz
  • Tatoeba-en-lt-train.tsv.gz
  • WikiMatrix-en-lt-train.tsv.gz
• Custom Scoris data set translated using Deepl.

Basic clean-up and deduplication was applied when creating this set

This can be used to train Lithuanian-English-Lithuanian MT Seq2Seq models.

Made by Scoris team

You can use this in the following way:

from datasets import load_dataset
dataset_name = "scoris/en-lt-merged-data" 

# Load the dataset
dataset = load_dataset(dataset_name)

# Accessing data
# Display the first example from the training set
print("First training example:", dataset['train'][0])

# Display the first example from the validation set
print("First validation example:", dataset['validation'][0])

# Iterate through a few examples from the training set
for i, example in enumerate(dataset['train']):
    if i < 5:
        print(f"Training example {i}:", example)
    else:
        break

# If you want to use the dataset in a machine learning model, you can directly
# iterate over the dataset or convert it to a pandas DataFrame for analysis
import pandas as pd

# Convert the training set to a pandas DataFrame
train_df = pd.DataFrame(dataset['train'])
print(train_df.head())