Model description (finetuned-kde4-en-to-fr)

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on the kde4 dataset. It achieves the following results on the evaluation set:

• Loss: 0.8556
• Bleu: 52.8853

Intended uses

• Translation of English text to French
• Generating coherent and accurate translations in the domain of technical computer science

Limitations

• The model's performance may degrade when translating sentences with complex or domain-specific terminology that was not present in the training data.
• It may struggle with idiomatic expressions and cultural nuances that are not captured in the training data.

Training and evaluation data

The model was fine-tuned on the KDE4 dataset, which consists of pairs of sentences in English and their French translations. The dataset contains 189,155 pairs for training and 21,018 pairs for validation.

Training procedure

The model was trained using the Seq2SeqTrainer API from the 🤗 Transformers library. The training procedure involved tokenizing the input English sentences and target French sentences, preparing the data collation for dynamic batching and fine-tuning the model. The evaluation metric used is SacreBLEU.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training details

Here's the data presented in a table format:

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3