| | --- |
| | license: mit |
| | base_model: facebook/m2m100_1.2B |
| | tags: |
| | - translation |
| | - generated_from_trainer |
| | datasets: |
| | - wmt16 |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: m2m100_1.2B |
| | 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: 33.3632 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # m2m100_1.2B |
| | |
| | This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2B) on the wmt16 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8189 |
| | - Bleu: 33.3632 |
| | - Gen Len: 36.176 |
| | |
| | ## 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: 1 |
| | - 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: 1 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
| | | 0.7163 | 1.0 | 47790 | 0.8189 | 33.3632 | 36.176 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
