<!-- 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. -->
mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.1
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: 0.9532
- Bleu: 45.1551
- Rouge: {'rouge1': 0.707093830119779, 'rouge2': 0.5240989044660875, 'rougeL': 0.6865395711179825, 'rougeLsum': 0.6867643949864491}
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 |
|---|---|---|---|---|---|
| 1.4485 | 1.0 | 4500 | 1.0236 | 42.1586 | {'rouge1': 0.6728104679322686, 'rouge2': 0.4866267759088613, 'rougeL': 0.6507619922873461, 'rougeLsum': 0.6508024989844624} |
| 0.8867 | 2.0 | 9000 | 0.9542 | 44.1945 | {'rouge1': 0.6933374960151913, 'rouge2': 0.5090654274262618, 'rougeL': 0.6722360570050694, 'rougeLsum': 0.6723972406375381} |
| 0.7112 | 3.0 | 13500 | 0.9408 | 44.9173 | {'rouge1': 0.7047659807760827, 'rouge2': 0.5200169348076622, 'rougeL': 0.6839031690668775, 'rougeLsum': 0.6842067045539153} |
| 0.6075 | 4.0 | 18000 | 0.9532 | 45.2020 | {'rouge1': 0.7070170730434684, 'rouge2': 0.5239391023023636, 'rougeL': 0.6863309446860562, 'rougeLsum': 0.6866635686411662} |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3
