metadata
library_name: transformers
base_model: facebook/mbart-large-cc25
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: 2ffdcffd70eb8f3c41bfbccd14df9209
results: []
2ffdcffd70eb8f3c41bfbccd14df9209
This model is a fine-tuned version of facebook/mbart-large-cc25 on the Helsinki-NLP/opus_books [de-en] dataset. It achieves the following results on the evaluation set:
- Loss: 2.3441
- Data Size: 1.0
- Epoch Runtime: 333.7994
- Bleu: 9.4162
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 | 9.3893 | 0 | 28.9578 | 0.2080 |
| No log | 1 | 1286 | 3.2857 | 0.0078 | 32.6526 | 8.1477 |
| 0.0727 | 2 | 2572 | 2.8567 | 0.0156 | 34.7107 | 7.3171 |
| 0.0807 | 3 | 3858 | 2.5293 | 0.0312 | 39.7063 | 5.9600 |
| 0.1113 | 4 | 5144 | 2.3319 | 0.0625 | 50.3564 | 6.8175 |
| 2.3098 | 5 | 6430 | 2.2014 | 0.125 | 69.8308 | 7.2238 |
| 2.1357 | 6 | 7716 | 2.0828 | 0.25 | 107.2597 | 8.8328 |
| 2.5511 | 7 | 9002 | 2.3429 | 0.5 | 184.3453 | 13.5245 |
| 1.872 | 8.0 | 10288 | 1.9355 | 1.0 | 334.1931 | 8.7933 |
| 1.6041 | 9.0 | 11574 | 1.8910 | 1.0 | 337.7265 | 9.7002 |
| 1.3249 | 10.0 | 12860 | 1.9350 | 1.0 | 334.5037 | 9.3442 |
| 1.0926 | 11.0 | 14146 | 2.0589 | 1.0 | 337.4164 | 8.8583 |
| 0.9308 | 12.0 | 15432 | 2.1886 | 1.0 | 334.9627 | 9.1417 |
| 0.7153 | 13.0 | 16718 | 2.3441 | 1.0 | 333.7994 | 9.4162 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1