--- license: mit base_model: kazandaev/m2m100_418M tags: - translation - generated_from_trainer datasets: - wmt16 metrics: - bleu model-index: - name: m2m100_418M results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: wmt16 type: wmt16 config: ru-en split: validation args: ru-en metrics: - name: Bleu type: bleu value: 32.0585 --- # m2m100_418M This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the custom en-ru dataset. It achieves the following results on the evaluation set: - Loss: 0.8954 - Bleu: 32.0585 - Gen Len: 36.1643 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 10 - total_train_batch_size: 40 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| | 0.8087 | 1.0 | 47790 | 0.9542 | 30.786 | 36.1469 | | 0.7266 | 2.0 | 95580 | 0.8954 | 32.0585 | 36.1643 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.2.0.dev20230920+cu121 - Datasets 2.14.4 - Tokenizers 0.13.3