metadata
library_name: transformers
license: mit
base_model: facebook/mbart-large-50
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: be37dcb56e0edd7abfdd701c1e6cf0df
results: []
be37dcb56e0edd7abfdd701c1e6cf0df
This model is a fine-tuned version of facebook/mbart-large-50 on the Helsinki-NLP/opus_books [de-en] dataset. It achieves the following results on the evaluation set:
- Loss: 2.3852
- Data Size: 1.0
- Epoch Runtime: 322.3205
- Bleu: 9.3174
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Bleu |
|---|---|---|---|---|---|---|
| No log | 0 | 0 | 6.2567 | 0 | 26.7048 | 1.6973 |
| No log | 1 | 1286 | 4.4748 | 0.0078 | 29.5383 | 5.0592 |
| 0.0895 | 2 | 2572 | 3.3679 | 0.0156 | 33.2817 | 10.4733 |
| 0.0899 | 3 | 3858 | 2.2590 | 0.0312 | 37.5992 | 6.7743 |
| 0.0993 | 4 | 5144 | 2.1548 | 0.0625 | 47.5234 | 8.0927 |
| 2.0738 | 5 | 6430 | 2.0462 | 0.125 | 66.0811 | 8.5674 |
| 1.9511 | 6 | 7716 | 1.9638 | 0.25 | 101.6687 | 11.8428 |
| 1.8928 | 7 | 9002 | 1.9670 | 0.5 | 176.5597 | 12.5154 |
| 1.8482 | 8.0 | 10288 | 1.8666 | 1.0 | 321.5913 | 9.3952 |
| 1.4755 | 9.0 | 11574 | 1.8589 | 1.0 | 322.5186 | 9.5484 |
| 1.2218 | 10.0 | 12860 | 1.9179 | 1.0 | 322.5333 | 9.4680 |
| 0.9689 | 11.0 | 14146 | 2.0313 | 1.0 | 322.2198 | 9.4077 |
| 0.8023 | 12.0 | 15432 | 2.2226 | 1.0 | 324.6607 | 9.6218 |
| 0.6054 | 13.0 | 16718 | 2.3852 | 1.0 | 322.3205 | 9.3174 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1