metadata
library_name: transformers
base_model: facebook/mbart-large-50-many-to-one-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: 2baf0c7fc011b0a22c6984d13a635a31
results: []
2baf0c7fc011b0a22c6984d13a635a31
This model is a fine-tuned version of facebook/mbart-large-50-many-to-one-mmt on the Helsinki-NLP/opus_books [en-es] dataset. It achieves the following results on the evaluation set:
- Loss: 2.2368
- Data Size: 1.0
- Epoch Runtime: 604.6076
- Bleu: 9.1969
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 | 5.8102 | 0 | 48.1224 | 0.6052 |
| No log | 1 | 2336 | 4.1491 | 0.0078 | 52.6214 | 1.5574 |
| 0.0627 | 2 | 4672 | 3.6285 | 0.0156 | 58.7082 | 2.6285 |
| 0.0805 | 3 | 7008 | 3.2199 | 0.0312 | 67.5729 | 3.4881 |
| 2.9332 | 4 | 9344 | 2.8721 | 0.0625 | 83.5089 | 4.6759 |
| 2.6498 | 5 | 11680 | 2.5635 | 0.125 | 117.1398 | 5.4796 |
| 2.2932 | 6 | 14016 | 2.2973 | 0.25 | 190.0217 | 6.9013 |
| 2.0659 | 7 | 16352 | 2.0638 | 0.5 | 329.6237 | 7.8104 |
| 1.8034 | 8.0 | 18688 | 1.9001 | 1.0 | 607.7954 | 8.3532 |
| 1.523 | 9.0 | 21024 | 1.8715 | 1.0 | 608.0761 | 9.7238 |
| 1.3197 | 10.0 | 23360 | 1.8835 | 1.0 | 608.2041 | 9.1238 |
| 1.1199 | 11.0 | 25696 | 1.9745 | 1.0 | 603.7367 | 8.8339 |
| 0.9434 | 12.0 | 28032 | 2.0606 | 1.0 | 606.0338 | 9.1520 |
| 0.7766 | 13.0 | 30368 | 2.2368 | 1.0 | 604.6076 | 9.1969 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1