File size: 2,669 Bytes
319c277 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
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_mid3
results: []
---
<!-- 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. -->
# ko-en_mbartLarge_mid3
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: 1.3246
- Bleu: 22.9623
- Gen Len: 18.7197
## 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: cosine_with_restarts
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.5377 | 0.23 | 2000 | 1.6122 | 17.2009 | 18.7106 |
| 1.3891 | 0.46 | 4000 | 1.5059 | 19.3345 | 18.7688 |
| 1.2812 | 0.7 | 6000 | 1.4348 | 20.6032 | 18.9022 |
| 1.2374 | 0.93 | 8000 | 1.4035 | 21.2391 | 18.8434 |
| 1.1734 | 1.16 | 10000 | 1.4039 | 21.304 | 18.9964 |
| 1.1531 | 1.39 | 12000 | 1.3694 | 21.9087 | 18.8573 |
| 1.1158 | 1.62 | 14000 | 1.3574 | 22.004 | 18.5485 |
| 1.0941 | 1.86 | 16000 | 1.3457 | 21.9785 | 18.7119 |
| 0.9809 | 2.09 | 18000 | 1.3495 | 22.7983 | 18.8011 |
| 0.9834 | 2.32 | 20000 | 1.3429 | 22.5654 | 18.9416 |
| 0.9981 | 2.55 | 22000 | 1.3246 | 22.9493 | 18.7364 |
| 1.0074 | 2.78 | 24000 | 1.3539 | 22.3874 | 18.4428 |
| 0.9752 | 3.02 | 26000 | 1.3587 | 22.1907 | 18.8139 |
| 0.8858 | 3.25 | 28000 | 1.3457 | 22.82 | 18.8021 |
| 0.8895 | 3.48 | 30000 | 1.3603 | 22.1575 | 18.5638 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
|