--- language: - ko - en base_model: facebook/mbart-large-50-many-to-many-mmt tags: - generated_from_trainer metrics: - bleu model-index: - name: ko-en_mbartLarge_exp20p_linear results: [] --- # ko-en_mbartLarge_exp20p_linear This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1514 - Bleu: 29.2703 - Gen Len: 18.512 ## 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: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2000 - num_epochs: 40 ### Training results | Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss | |:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:| | 1.3977 | 0.46 | 4000 | 22.7153 | 18.7135 | 1.3720 | | 1.2824 | 0.93 | 8000 | 24.8579 | 18.7821 | 1.2633 | | 1.1989 | 1.39 | 12000 | 26.2533 | 18.7975 | 1.2069 | | 1.1534 | 1.86 | 16000 | 26.1503 | 19.2075 | 1.1907 | | 1.0245 | 2.32 | 20000 | 27.8764 | 18.6046 | 1.1464 | | 1.0186 | 2.78 | 24000 | 28.4585 | 18.6731 | 1.1286 | | 0.9245 | 3.25 | 28000 | 1.1264 | 28.4834 | 18.5428 | | 0.9343 | 3.71 | 32000 | 1.1182 | 28.8235 | 18.7833 | | 0.8215 | 4.18 | 36000 | 1.1331 | 28.6134 | 18.5656 | | 0.8456 | 4.64 | 40000 | 1.1203 | 28.7324 | 18.459 | | 0.7437 | 5.11 | 44000 | 1.1458 | 28.7297 | 18.7835 | | 0.7829 | 5.57 | 48000 | 1.1367 | 28.8328 | 18.6052 | | 0.7434 | 6.03 | 52000 | 1.1697 | 28.2106 | 18.4871 | | 0.7153 | 6.5 | 56000 | 1.1771 | 28.1455 | 18.7413 | | 0.6996 | 6.96 | 60000 | 1.1514 | 29.2694 | 18.5162 | | 0.6336 | 7.43 | 64000 | 1.2213 | 28.1465 | 18.5439 | | 0.7218 | 7.89 | 68000 | 1.1835 | 28.2245 | 18.5246 | | 0.5934 | 8.35 | 72000 | 1.2387 | 28.3836 | 18.6717 | | 0.5723 | 8.82 | 76000 | 1.2323 | 28.5925 | 18.5566 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.14.5 - Tokenizers 0.14.1