metadata
license: mit
base_model: facebook/mbart-large-50
tags:
- translation
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.01
results: []
mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.01
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9547
- Bleu: 45.0896
- Rouge: {'rouge1': 0.7050843983318068, 'rouge2': 0.5221826018405332, 'rougeL': 0.6843669248955093, 'rougeLsum': 0.6845499780252107}
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge |
|---|---|---|---|---|---|
| 1.4571 | 1.0 | 4500 | 1.0262 | 41.9188 | {'rouge1': 0.6701489298042851, 'rouge2': 0.4850120961190509, 'rougeL': 0.6479081216501843, 'rougeLsum': 0.6480345623292922} |
| 0.889 | 2.0 | 9000 | 0.9559 | 44.3378 | {'rouge1': 0.6920481616267358, 'rouge2': 0.5087283264258592, 'rougeL': 0.6709294966142768, 'rougeLsum': 0.6710449317682404} |
| 0.7134 | 3.0 | 13500 | 0.9416 | 44.9705 | {'rouge1': 0.7026762914671131, 'rouge2': 0.5192700210995049, 'rougeL': 0.6817974408692513, 'rougeLsum': 0.6819680202609157} |
| 0.6098 | 4.0 | 18000 | 0.9547 | 45.1741 | {'rouge1': 0.7051668954804624, 'rouge2': 0.5222186626492409, 'rougeL': 0.6844002112351866, 'rougeLsum': 0.6845851183829141} |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3