| # ALERT!!! | |
| [leadawon/jeju-ko-nmt-v6](https://huggingface.co/leadawon/jeju-ko-nmt-v6) is better than leadawon/jeju-ko-nmt-v8 | |
| 6๋ฒ์ ์ฑ๋ฅ์ด ๋ ์ข์ต๋๋ค!!!!!!!!!!!!!!!!!!!!!!!!!!!!! | |
| # tag | |
| --- | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: jeju-ko-nmt-v8 | |
| 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. --> | |
| # jeju-ko-nmt-v8 | |
| This model is a fine-tuned version of [leadawon/jeju-ko-nmt-v7](https://huggingface.co/leadawon/jeju-ko-nmt-v7) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2448 | |
| ## 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-06 | |
| - train_batch_size: 24 | |
| - eval_batch_size: 24 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 96 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:-----:|:---------------:| | |
| | 0.2684 | 0.04 | 500 | 0.2568 | | |
| | 0.2468 | 0.08 | 1000 | 0.2547 | | |
| | 0.2167 | 0.12 | 1500 | 0.2540 | | |
| | 0.1966 | 0.16 | 2000 | 0.2535 | | |
| | 0.1846 | 0.2 | 2500 | 0.2533 | | |
| | 0.1727 | 0.24 | 3000 | 0.2535 | | |
| | 0.1746 | 0.28 | 3500 | 0.2522 | | |
| | 0.1726 | 0.32 | 4000 | 0.2521 | | |
| | 0.1722 | 0.36 | 4500 | 0.2519 | | |
| | 0.1731 | 0.4 | 5000 | 0.2515 | | |
| | 0.1701 | 0.44 | 5500 | 0.2518 | | |
| | 0.168 | 0.48 | 6000 | 0.2515 | | |
| | 0.1706 | 0.52 | 6500 | 0.2509 | | |
| | 0.1659 | 0.56 | 7000 | 0.2514 | | |
| | 0.1702 | 0.6 | 7500 | 0.2509 | | |
| | 0.1667 | 0.64 | 8000 | 0.2510 | | |
| | 0.1661 | 0.68 | 8500 | 0.2508 | | |
| | 0.1647 | 0.72 | 9000 | 0.2510 | | |
| | 0.1632 | 0.76 | 9500 | 0.2510 | | |
| | 0.1655 | 0.8 | 10000 | 0.2506 | | |
| | 0.1645 | 0.84 | 10500 | 0.2508 | | |
| | 0.1617 | 0.88 | 11000 | 0.2508 | | |
| | 0.1627 | 0.91 | 11500 | 0.2511 | | |
| | 0.2764 | 0.95 | 12000 | 0.2478 | | |
| | 0.2755 | 0.99 | 12500 | 0.2462 | | |
| | 0.2275 | 1.03 | 13000 | 0.2464 | | |
| | 0.2201 | 1.07 | 13500 | 0.2463 | | |
| | 0.2207 | 1.11 | 14000 | 0.2463 | | |
| | 0.2202 | 1.15 | 14500 | 0.2462 | | |
| | 0.2194 | 1.19 | 15000 | 0.2460 | | |
| | 0.2177 | 1.23 | 15500 | 0.2461 | | |
| | 0.2187 | 1.27 | 16000 | 0.2460 | | |
| | 0.2184 | 1.31 | 16500 | 0.2459 | | |
| | 0.2182 | 1.35 | 17000 | 0.2457 | | |
| | 0.219 | 1.39 | 17500 | 0.2458 | | |
| | 0.2206 | 1.43 | 18000 | 0.2455 | | |
| | 0.2211 | 1.47 | 18500 | 0.2455 | | |
| | 0.2164 | 1.51 | 19000 | 0.2455 | | |
| | 0.2202 | 1.55 | 19500 | 0.2454 | | |
| | 0.2208 | 1.59 | 20000 | 0.2452 | | |
| | 0.2208 | 1.63 | 20500 | 0.2450 | | |
| | 0.2204 | 1.67 | 21000 | 0.2450 | | |
| | 0.2193 | 1.71 | 21500 | 0.2450 | | |
| | 0.221 | 1.75 | 22000 | 0.2451 | | |
| | 0.2168 | 1.79 | 22500 | 0.2450 | | |
| | 0.2169 | 1.83 | 23000 | 0.2449 | | |
| | 0.218 | 1.87 | 23500 | 0.2449 | | |
| | 0.2196 | 1.91 | 24000 | 0.2449 | | |
| | 0.2218 | 1.95 | 24500 | 0.2448 | | |
| | 0.2199 | 1.99 | 25000 | 0.2448 | | |
| ### Framework versions | |
| - Transformers 4.26.0 | |
| - Pytorch 1.13.1+cu116 | |
| - Tokenizers 0.13.2 | |