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ko-en_mbartLarge_exp10p
yesj1234/ko-en_mbartLarge_exp10p
ko-en_mbartLarge_exp10p is a machine learning model from yesj1234. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mbart
- Access
- Public
- Created
- Oct 19, 2023
- Updated
- Oct 19, 2023
- SHA
- 894c861d
Base models
Model card
From the Hugging Face model README
<!-- 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_exp10p
This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1770
- Bleu: 27.7431
- Gen Len: 18.6157
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 |
|---|---|---|---|---|---|
| 1.5087 | 0.46 | 2000 | 1.4383 | 21.689 | 18.6869 |
| 1.3739 | 0.93 | 4000 | 1.3328 | 23.8363 | 18.7463 |
| 1.2585 | 1.39 | 6000 | 1.2720 | 24.7319 | 18.4624 |
| 1.2355 | 1.86 | 8000 | 1.2356 | 26.1612 | 18.484 |
| 1.0973 | 2.32 | 10000 | 1.2074 | 26.6567 | 18.554 |
| 1.1157 | 2.78 | 12000 | 1.2069 | 26.4733 | 18.8044 |
| 0.9631 | 3.25 | 14000 | 1.1901 | 27.1062 | 18.6803 |
| 1.0223 | 3.71 | 16000 | 1.2280 | 26.3038 | 18.7993 |
| 0.8621 | 4.18 | 18000 | 1.2185 | 26.8035 | 18.6679 |
| 0.866 | 4.64 | 20000 | 1.1770 | 27.7431 | 18.6157 |
| 0.7063 | 5.11 | 22000 | 1.2176 | 27.7268 | 18.6026 |
| 0.7504 | 5.57 | 24000 | 1.2268 | 27.053 | 18.5299 |
| 0.6986 | 6.03 | 26000 | 1.2739 | 27.5119 | 18.7806 |
| 0.6193 | 6.5 | 28000 | 1.2745 | 27.3877 | 18.5109 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
- Library
- transformers
- Type
- mbart
- Languages
- ko, en
- Created
- Oct 19, 2023
- Updated
- Oct 19, 2023