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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: MIX2_ja-en_helsinki
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. -->
# MIX2_ja-en_helsinki
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ja-en](https://huggingface.co/Helsinki-NLP/opus-mt-ja-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4929
- Otaku Benchmark VN BLEU: 20.21
- Otaku Benchmark LN BLEU: 13.29
- Otaku Benchmark MANGA BLEU: 19.07
## 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: 0.0003
- train_batch_size: 96
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.8467 | 0.01 | 2000 | 2.3237 |
| 2.6439 | 0.02 | 4000 | 2.2542 |
| 2.547 | 0.03 | 6000 | 2.1956 |
| 2.4852 | 0.04 | 8000 | 2.1088 |
| 2.4408 | 0.05 | 10000 | 2.0909 |
| 2.404 | 0.06 | 12000 | 2.1029 |
| 2.3634 | 0.07 | 14000 | 2.0636 |
| 2.3491 | 0.08 | 16000 | 2.0312 |
| 2.3203 | 0.09 | 18000 | 2.0187 |
| 2.3002 | 0.1 | 20000 | 1.9999 |
| 2.2791 | 0.11 | 22000 | 1.9823 |
| 2.2607 | 0.11 | 24000 | 1.9588 |
| 2.2475 | 0.12 | 26000 | 1.9728 |
| 2.2308 | 0.13 | 28000 | 1.9330 |
| 2.2237 | 0.14 | 30000 | 1.9657 |
| 2.208 | 0.15 | 32000 | 1.9560 |
| 2.2019 | 0.16 | 34000 | 1.9704 |
| 2.1864 | 0.17 | 36000 | 1.9513 |
| 2.1764 | 0.18 | 38000 | 1.9534 |
| 2.163 | 0.19 | 40000 | 1.9140 |
| 2.1534 | 0.2 | 42000 | 1.9241 |
| 2.146 | 0.21 | 44000 | 1.9162 |
| 2.1403 | 0.22 | 46000 | 1.9030 |
| 2.1309 | 0.23 | 48000 | 1.8741 |
| 2.1174 | 0.24 | 50000 | 1.8834 |
| 2.1157 | 0.25 | 52000 | 1.8666 |
| 2.1116 | 0.26 | 54000 | 1.8870 |
| 2.1062 | 0.27 | 56000 | 1.8837 |
| 2.0994 | 0.28 | 58000 | 1.8638 |
| 2.0924 | 0.29 | 60000 | 1.8766 |
| 2.0874 | 0.3 | 62000 | 1.8712 |
| 2.0805 | 0.31 | 64000 | 1.8792 |
| 2.0746 | 0.32 | 66000 | 1.8586 |
| 2.0684 | 0.32 | 68000 | 1.8819 |
| 2.0678 | 0.33 | 70000 | 1.8529 |
| 2.061 | 0.34 | 72000 | 1.8219 |
| 2.0532 | 0.35 | 74000 | 1.8383 |
| 2.0536 | 0.36 | 76000 | 1.8273 |
| 2.0432 | 0.37 | 78000 | 1.8304 |
| 2.0386 | 0.38 | 80000 | 1.8208 |
| 2.0361 | 0.39 | 82000 | 1.8103 |
| 2.0353 | 0.4 | 84000 | 1.8193 |
| 2.0266 | 0.41 | 86000 | 1.8369 |
| 2.0277 | 0.42 | 88000 | 1.8266 |
| 2.0221 | 0.43 | 90000 | 1.8372 |
| 2.0181 | 0.44 | 92000 | 1.8436 |
| 2.0182 | 0.45 | 94000 | 1.8505 |
| 2.0088 | 0.46 | 96000 | 1.8127 |
| 2.005 | 0.47 | 98000 | 1.8325 |
| 2.0003 | 0.48 | 100000 | 1.8407 |
| 2.0031 | 0.49 | 102000 | 1.8140 |
| 1.9954 | 0.5 | 104000 | 1.8177 |
| 1.9894 | 0.51 | 106000 | 1.8072 |
| 1.9901 | 0.52 | 108000 | 1.7971 |
| 1.9864 | 0.53 | 110000 | 1.8007 |
| 1.9848 | 0.53 | 112000 | 1.7961 |
| 1.9774 | 0.54 | 114000 | 1.7933 |
| 1.9802 | 0.55 | 116000 | 1.8031 |
| 1.9698 | 0.56 | 118000 | 1.8137 |
| 1.973 | 0.57 | 120000 | 1.7930 |
| 1.9696 | 0.58 | 122000 | 1.7838 |
| 1.9641 | 0.59 | 124000 | 1.7730 |
| 1.9609 | 0.6 | 126000 | 1.7800 |
| 1.9605 | 0.61 | 128000 | 1.7680 |
| 1.9516 | 0.62 | 130000 | 1.7895 |
| 1.9529 | 0.63 | 132000 | 1.7825 |
| 1.9503 | 0.64 | 134000 | 1.7792 |
| 1.9528 | 0.65 | 136000 | 1.8031 |
| 1.9439 | 0.66 | 138000 | 1.7652 |
| 1.9453 | 0.67 | 140000 | 1.7713 |
| 1.9404 | 0.68 | 142000 | 1.7585 |
| 1.9399 | 0.69 | 144000 | 1.7454 |
| 1.9325 | 0.7 | 146000 | 1.7605 |
| 1.9327 | 0.71 | 148000 | 1.7608 |
| 1.9301 | 0.72 | 150000 | 1.7743 |
| 1.928 | 0.73 | 152000 | 1.7532 |
| 1.9286 | 0.74 | 154000 | 1.7682 |
| 1.9194 | 0.74 | 156000 | 1.7582 |
| 1.9247 | 0.75 | 158000 | 1.7601 |
| 1.9183 | 0.76 | 160000 | 1.7600 |
| 1.9138 | 0.77 | 162000 | 1.7555 |
| 1.9148 | 0.78 | 164000 | 1.7447 |
| 1.913 | 0.79 | 166000 | 1.7512 |
| 1.9084 | 0.8 | 168000 | 1.7408 |
| 1.9109 | 0.81 | 170000 | 1.7463 |
| 1.905 | 0.82 | 172000 | 1.7543 |
| 1.9067 | 0.83 | 174000 | 1.7662 |
| 1.9005 | 0.84 | 176000 | 1.7428 |
| 1.8997 | 0.85 | 178000 | 1.7500 |
| 1.8963 | 0.86 | 180000 | 1.7297 |
| 1.8938 | 0.87 | 182000 | 1.7356 |
| 1.8923 | 0.88 | 184000 | 1.7602 |
| 1.8896 | 0.89 | 186000 | 1.7426 |
| 1.8866 | 0.9 | 188000 | 1.7323 |
| 1.887 | 0.91 | 190000 | 1.7587 |
| 1.8855 | 0.92 | 192000 | 1.7591 |
| 1.8842 | 0.93 | 194000 | 1.7570 |
| 1.8808 | 0.94 | 196000 | 1.7311 |
| 1.8836 | 0.95 | 198000 | 1.7449 |
| 1.8761 | 0.96 | 200000 | 1.7534 |
| 1.8721 | 0.96 | 202000 | 1.7623 |
| 1.8765 | 0.97 | 204000 | 1.7462 |
| 1.8747 | 0.98 | 206000 | 1.7452 |
| 1.8667 | 0.99 | 208000 | 1.7303 |
| 1.8618 | 1.0 | 210000 | 1.7468 |
| 1.8475 | 1.01 | 212000 | 1.7443 |
| 1.8435 | 1.02 | 214000 | 1.7622 |
| 1.8452 | 1.03 | 216000 | 1.7153 |
| 1.84 | 1.04 | 218000 | 1.6976 |
| 1.8432 | 1.05 | 220000 | 1.7013 |
| 1.842 | 1.06 | 222000 | 1.7073 |
| 1.8428 | 1.07 | 224000 | 1.6991 |
| 1.841 | 1.08 | 226000 | 1.7477 |
| 1.8321 | 1.09 | 228000 | 1.7438 |
| 1.838 | 1.1 | 230000 | 1.7352 |
| 1.8339 | 1.11 | 232000 | 1.7242 |
| 1.836 | 1.12 | 234000 | 1.7221 |
| 1.8329 | 1.13 | 236000 | 1.7402 |
| 1.8337 | 1.14 | 238000 | 1.7083 |
| 1.8267 | 1.15 | 240000 | 1.7200 |
| 1.8335 | 1.16 | 242000 | 1.7092 |
| 1.8306 | 1.17 | 244000 | 1.7340 |
| 1.8279 | 1.17 | 246000 | 1.6983 |
| 1.8261 | 1.18 | 248000 | 1.6928 |
| 1.8295 | 1.19 | 250000 | 1.7135 |
| 1.8227 | 1.2 | 252000 | 1.7156 |
| 1.822 | 1.21 | 254000 | 1.7018 |
| 1.8216 | 1.22 | 256000 | 1.7157 |
| 1.8205 | 1.23 | 258000 | 1.7047 |
| 1.8163 | 1.24 | 260000 | 1.6988 |
| 1.8187 | 1.25 | 262000 | 1.7077 |
| 1.8188 | 1.26 | 264000 | 1.6859 |
| 1.8138 | 1.27 | 266000 | 1.6831 |
| 1.8173 | 1.28 | 268000 | 1.6887 |
| 1.813 | 1.29 | 270000 | 1.6967 |
| 1.8114 | 1.3 | 272000 | 1.7085 |
| 1.8057 | 1.31 | 274000 | 1.6885 |
| 1.8094 | 1.32 | 276000 | 1.7198 |
| 1.8079 | 1.33 | 278000 | 1.7036 |
| 1.8056 | 1.34 | 280000 | 1.7106 |
| 1.8044 | 1.35 | 282000 | 1.6704 |
| 1.8047 | 1.36 | 284000 | 1.6811 |
| 1.7978 | 1.37 | 286000 | 1.6848 |
| 1.7997 | 1.38 | 288000 | 1.6698 |
| 1.7997 | 1.38 | 290000 | 1.6820 |
| 1.7945 | 1.39 | 292000 | 1.6963 |
| 1.7958 | 1.4 | 294000 | 1.6922 |
| 1.7923 | 1.41 | 296000 | 1.6577 |
| 1.7975 | 1.42 | 298000 | 1.6621 |
| 1.7914 | 1.43 | 300000 | 1.6804 |
| 1.7944 | 1.44 | 302000 | 1.6953 |
| 1.7927 | 1.45 | 304000 | 1.6846 |
| 1.789 | 1.46 | 306000 | 1.6889 |
| 1.7851 | 1.47 | 308000 | 1.6652 |
| 1.7902 | 1.48 | 310000 | 1.6823 |
| 1.7873 | 1.49 | 312000 | 1.6603 |
| 1.7868 | 1.5 | 314000 | 1.6766 |
| 1.7856 | 1.51 | 316000 | 1.6717 |
| 1.7807 | 1.52 | 318000 | 1.6466 |
| 1.7767 | 1.53 | 320000 | 1.6639 |
| 1.7782 | 1.54 | 322000 | 1.6678 |
| 1.7762 | 1.55 | 324000 | 1.6853 |
| 1.7746 | 1.56 | 326000 | 1.6785 |
| 1.7746 | 1.57 | 328000 | 1.6777 |
| 1.7716 | 1.58 | 330000 | 1.6784 |
| 1.7699 | 1.59 | 332000 | 1.6648 |
| 1.7739 | 1.59 | 334000 | 1.6725 |
| 1.7703 | 1.6 | 336000 | 1.6915 |
| 1.7707 | 1.61 | 338000 | 1.6858 |
| 1.7619 | 1.62 | 340000 | 1.6624 |
| 1.7652 | 1.63 | 342000 | 1.6797 |
| 1.7626 | 1.64 | 344000 | 1.6728 |
| 1.7647 | 1.65 | 346000 | 1.6580 |
| 1.7616 | 1.66 | 348000 | 1.6679 |
| 1.7616 | 1.67 | 350000 | 1.6470 |
| 1.7611 | 1.68 | 352000 | 1.6489 |
| 1.759 | 1.69 | 354000 | 1.6603 |
| 1.7604 | 1.7 | 356000 | 1.6532 |
| 1.7599 | 1.71 | 358000 | 1.6477 |
| 1.7529 | 1.72 | 360000 | 1.6322 |
| 1.7596 | 1.73 | 362000 | 1.6447 |
| 1.7508 | 1.74 | 364000 | 1.6509 |
| 1.7533 | 1.75 | 366000 | 1.6465 |
| 1.755 | 1.76 | 368000 | 1.6485 |
| 1.7473 | 1.77 | 370000 | 1.6493 |
| 1.7435 | 1.78 | 372000 | 1.6542 |
| 1.7483 | 1.79 | 374000 | 1.6573 |
| 1.7475 | 1.8 | 376000 | 1.6626 |
| 1.7439 | 1.8 | 378000 | 1.6366 |
| 1.7417 | 1.81 | 380000 | 1.6312 |
| 1.7387 | 1.82 | 382000 | 1.6424 |
| 1.7415 | 1.83 | 384000 | 1.6468 |
| 1.7409 | 1.84 | 386000 | 1.6528 |
| 1.7362 | 1.85 | 388000 | 1.6394 |
| 1.7372 | 1.86 | 390000 | 1.6581 |
| 1.7347 | 1.87 | 392000 | 1.6546 |
| 1.7368 | 1.88 | 394000 | 1.6468 |
| 1.7302 | 1.89 | 396000 | 1.6450 |
| 1.7317 | 1.9 | 398000 | 1.6368 |
| 1.7306 | 1.91 | 400000 | 1.6399 |
| 1.7304 | 1.92 | 402000 | 1.6180 |
| 1.726 | 1.93 | 404000 | 1.6212 |
| 1.7271 | 1.94 | 406000 | 1.6302 |
| 1.7312 | 1.95 | 408000 | 1.6264 |
| 1.7249 | 1.96 | 410000 | 1.6584 |
| 1.7226 | 1.97 | 412000 | 1.6514 |
| 1.7214 | 1.98 | 414000 | 1.6516 |
| 1.7228 | 1.99 | 416000 | 1.6346 |
| 1.7205 | 2.0 | 418000 | 1.6370 |
| 1.7041 | 2.01 | 420000 | 1.6021 |
| 1.691 | 2.02 | 422000 | 1.6385 |
| 1.6896 | 2.02 | 424000 | 1.6280 |
| 1.6882 | 2.03 | 426000 | 1.6295 |
| 1.6889 | 2.04 | 428000 | 1.6445 |
| 1.6904 | 2.05 | 430000 | 1.6558 |
| 1.6933 | 2.06 | 432000 | 1.6164 |
| 1.6916 | 2.07 | 434000 | 1.6011 |
| 1.6873 | 2.08 | 436000 | 1.6199 |
| 1.6903 | 2.09 | 438000 | 1.6300 |
| 1.6859 | 2.1 | 440000 | 1.6104 |
| 1.6901 | 2.11 | 442000 | 1.6248 |
| 1.6884 | 2.12 | 444000 | 1.6251 |
| 1.6859 | 2.13 | 446000 | 1.6145 |
| 1.6906 | 2.14 | 448000 | 1.6181 |
| 1.6859 | 2.15 | 450000 | 1.6264 |
| 1.6814 | 2.16 | 452000 | 1.6069 |
| 1.6853 | 2.17 | 454000 | 1.6089 |
| 1.6881 | 2.18 | 456000 | 1.6102 |
| 1.6869 | 2.19 | 458000 | 1.6327 |
| 1.6827 | 2.2 | 460000 | 1.6069 |
| 1.6813 | 2.21 | 462000 | 1.6278 |
| 1.6806 | 2.22 | 464000 | 1.6176 |
| 1.6763 | 2.23 | 466000 | 1.6180 |
| 1.68 | 2.23 | 468000 | 1.6226 |
| 1.6816 | 2.24 | 470000 | 1.6071 |
| 1.6845 | 2.25 | 472000 | 1.6178 |
| 1.6764 | 2.26 | 474000 | 1.6073 |
| 1.682 | 2.27 | 476000 | 1.5966 |
| 1.6727 | 2.28 | 478000 | 1.5979 |
| 1.6718 | 2.29 | 480000 | 1.6109 |
| 1.6764 | 2.3 | 482000 | 1.6034 |
| 1.671 | 2.31 | 484000 | 1.6001 |
| 1.6691 | 2.32 | 486000 | 1.6148 |
| 1.6706 | 2.33 | 488000 | 1.6003 |
| 1.6705 | 2.34 | 490000 | 1.6021 |
| 1.6699 | 2.35 | 492000 | 1.5940 |
| 1.6708 | 2.36 | 494000 | 1.6077 |
| 1.6715 | 2.37 | 496000 | 1.6188 |
| 1.6672 | 2.38 | 498000 | 1.5903 |
| 1.6638 | 2.39 | 500000 | 1.6042 |
| 1.6634 | 2.4 | 502000 | 1.5967 |
| 1.6669 | 2.41 | 504000 | 1.5904 |
| 1.6643 | 2.42 | 506000 | 1.6071 |
| 1.6606 | 2.43 | 508000 | 1.6065 |
| 1.6573 | 2.44 | 510000 | 1.6010 |
| 1.6603 | 2.44 | 512000 | 1.5801 |
| 1.6568 | 2.45 | 514000 | 1.5961 |
| 1.6564 | 2.46 | 516000 | 1.6020 |
| 1.6596 | 2.47 | 518000 | 1.5952 |
| 1.6567 | 2.48 | 520000 | 1.5760 |
| 1.6536 | 2.49 | 522000 | 1.5697 |
| 1.6564 | 2.5 | 524000 | 1.5664 |
| 1.652 | 2.51 | 526000 | 1.5616 |
| 1.653 | 2.52 | 528000 | 1.5738 |
| 1.6525 | 2.53 | 530000 | 1.5754 |
| 1.65 | 2.54 | 532000 | 1.5749 |
| 1.6519 | 2.55 | 534000 | 1.5788 |
| 1.6515 | 2.56 | 536000 | 1.5953 |
| 1.6492 | 2.57 | 538000 | 1.5836 |
| 1.6473 | 2.58 | 540000 | 1.5896 |
| 1.6452 | 2.59 | 542000 | 1.5858 |
| 1.6464 | 2.6 | 544000 | 1.5760 |
| 1.6445 | 2.61 | 546000 | 1.5683 |
| 1.6457 | 2.62 | 548000 | 1.5823 |
| 1.6417 | 2.63 | 550000 | 1.5780 |
| 1.6407 | 2.64 | 552000 | 1.5715 |
| 1.6368 | 2.65 | 554000 | 1.5618 |
| 1.6357 | 2.65 | 556000 | 1.5725 |
| 1.6446 | 2.66 | 558000 | 1.5744 |
| 1.634 | 2.67 | 560000 | 1.5360 |
| 1.6351 | 2.68 | 562000 | 1.5599 |
| 1.6362 | 2.69 | 564000 | 1.5607 |
| 1.637 | 2.7 | 566000 | 1.5561 |
| 1.6324 | 2.71 | 568000 | 1.5591 |
| 1.6325 | 2.72 | 570000 | 1.5527 |
| 1.6323 | 2.73 | 572000 | 1.5537 |
| 1.629 | 2.74 | 574000 | 1.5673 |
| 1.627 | 2.75 | 576000 | 1.5509 |
| 1.6279 | 2.76 | 578000 | 1.5507 |
| 1.6291 | 2.77 | 580000 | 1.5304 |
| 1.625 | 2.78 | 582000 | 1.5540 |
| 1.6246 | 2.79 | 584000 | 1.5530 |
| 1.6228 | 2.8 | 586000 | 1.5570 |
| 1.6241 | 2.81 | 588000 | 1.5586 |
| 1.6224 | 2.82 | 590000 | 1.5480 |
| 1.6264 | 2.83 | 592000 | 1.5624 |
| 1.6214 | 2.84 | 594000 | 1.5565 |
| 1.6187 | 2.85 | 596000 | 1.5397 |
| 1.6191 | 2.86 | 598000 | 1.5520 |
| 1.6192 | 2.87 | 600000 | 1.5494 |
| 1.6182 | 2.87 | 602000 | 1.5608 |
| 1.6164 | 2.88 | 604000 | 1.5428 |
| 1.6107 | 2.89 | 606000 | 1.5525 |
| 1.614 | 2.9 | 608000 | 1.5277 |
| 1.6158 | 2.91 | 610000 | 1.5502 |
| 1.6082 | 2.92 | 612000 | 1.5452 |
| 1.6089 | 2.93 | 614000 | 1.5400 |
| 1.6112 | 2.94 | 616000 | 1.5322 |
| 1.6069 | 2.95 | 618000 | 1.5394 |
| 1.6111 | 2.96 | 620000 | 1.5537 |
| 1.6038 | 2.97 | 622000 | 1.5486 |
| 1.6073 | 2.98 | 624000 | 1.5551 |
| 1.6046 | 2.99 | 626000 | 1.5386 |
| 1.6051 | 3.0 | 628000 | 1.5369 |
| 1.5672 | 3.01 | 630000 | 1.5361 |
| 1.5694 | 3.02 | 632000 | 1.5390 |
| 1.5692 | 3.03 | 634000 | 1.5386 |
| 1.5651 | 3.04 | 636000 | 1.5456 |
| 1.5724 | 3.05 | 638000 | 1.5419 |
| 1.5708 | 3.06 | 640000 | 1.5363 |
| 1.5665 | 3.07 | 642000 | 1.5446 |
| 1.5706 | 3.08 | 644000 | 1.5331 |
| 1.5679 | 3.08 | 646000 | 1.5449 |
| 1.5678 | 3.09 | 648000 | 1.5436 |
| 1.5676 | 3.1 | 650000 | 1.5309 |
| 1.5657 | 3.11 | 652000 | 1.5334 |
| 1.5697 | 3.12 | 654000 | 1.5303 |
| 1.5617 | 3.13 | 656000 | 1.5380 |
| 1.5675 | 3.14 | 658000 | 1.5404 |
| 1.5612 | 3.15 | 660000 | 1.5258 |
| 1.5639 | 3.16 | 662000 | 1.5329 |
| 1.567 | 3.17 | 664000 | 1.5418 |
| 1.5619 | 3.18 | 666000 | 1.5314 |
| 1.5637 | 3.19 | 668000 | 1.5201 |
| 1.5608 | 3.2 | 670000 | 1.5181 |
| 1.5641 | 3.21 | 672000 | 1.5290 |
| 1.5626 | 3.22 | 674000 | 1.5180 |
| 1.5605 | 3.23 | 676000 | 1.5156 |
| 1.5566 | 3.24 | 678000 | 1.5266 |
| 1.5587 | 3.25 | 680000 | 1.5286 |
| 1.5602 | 3.26 | 682000 | 1.5265 |
| 1.5535 | 3.27 | 684000 | 1.5354 |
| 1.5589 | 3.28 | 686000 | 1.5265 |
| 1.5569 | 3.29 | 688000 | 1.5346 |
| 1.559 | 3.29 | 690000 | 1.5306 |
| 1.5507 | 3.3 | 692000 | 1.5359 |
| 1.5547 | 3.31 | 694000 | 1.5264 |
| 1.5498 | 3.32 | 696000 | 1.5264 |
| 1.5559 | 3.33 | 698000 | 1.5273 |
| 1.553 | 3.34 | 700000 | 1.5137 |
| 1.5503 | 3.35 | 702000 | 1.5143 |
| 1.5498 | 3.36 | 704000 | 1.5263 |
| 1.5516 | 3.37 | 706000 | 1.5096 |
| 1.5461 | 3.38 | 708000 | 1.5112 |
| 1.5489 | 3.39 | 710000 | 1.5094 |
| 1.5451 | 3.4 | 712000 | 1.5079 |
| 1.544 | 3.41 | 714000 | 1.5058 |
| 1.5446 | 3.42 | 716000 | 1.5005 |
| 1.5417 | 3.43 | 718000 | 1.4972 |
| 1.5469 | 3.44 | 720000 | 1.5043 |
| 1.5407 | 3.45 | 722000 | 1.5041 |
| 1.5484 | 3.46 | 724000 | 1.5104 |
| 1.5409 | 3.47 | 726000 | 1.5087 |
| 1.5431 | 3.48 | 728000 | 1.5114 |
| 1.5393 | 3.49 | 730000 | 1.5102 |
| 1.5364 | 3.5 | 732000 | 1.5143 |
| 1.5403 | 3.5 | 734000 | 1.5202 |
| 1.5386 | 3.51 | 736000 | 1.5143 |
| 1.5381 | 3.52 | 738000 | 1.5198 |
| 1.5341 | 3.53 | 740000 | 1.5136 |
| 1.5344 | 3.54 | 742000 | 1.5172 |
| 1.5347 | 3.55 | 744000 | 1.5149 |
| 1.5292 | 3.56 | 746000 | 1.5141 |
| 1.5344 | 3.57 | 748000 | 1.5066 |
| 1.5307 | 3.58 | 750000 | 1.5087 |
| 1.5324 | 3.59 | 752000 | 1.5113 |
| 1.5273 | 3.6 | 754000 | 1.5101 |
| 1.5273 | 3.61 | 756000 | 1.4975 |
| 1.5282 | 3.62 | 758000 | 1.5053 |
| 1.5252 | 3.63 | 760000 | 1.4998 |
| 1.525 | 3.64 | 762000 | 1.5020 |
| 1.5297 | 3.65 | 764000 | 1.5075 |
| 1.5215 | 3.66 | 766000 | 1.4980 |
| 1.5237 | 3.67 | 768000 | 1.5066 |
| 1.5248 | 3.68 | 770000 | 1.5093 |
| 1.5231 | 3.69 | 772000 | 1.5090 |
| 1.5224 | 3.7 | 774000 | 1.5093 |
| 1.526 | 3.71 | 776000 | 1.5015 |
| 1.5215 | 3.71 | 778000 | 1.5045 |
| 1.5231 | 3.72 | 780000 | 1.4971 |
| 1.5205 | 3.73 | 782000 | 1.4987 |
| 1.5171 | 3.74 | 784000 | 1.5001 |
| 1.5134 | 3.75 | 786000 | 1.4951 |
| 1.5155 | 3.76 | 788000 | 1.4975 |
| 1.5154 | 3.77 | 790000 | 1.4928 |
| 1.5167 | 3.78 | 792000 | 1.4983 |
| 1.5146 | 3.79 | 794000 | 1.4938 |
| 1.5138 | 3.8 | 796000 | 1.4985 |
| 1.5137 | 3.81 | 798000 | 1.5021 |
| 1.5111 | 3.82 | 800000 | 1.5020 |
| 1.5134 | 3.83 | 802000 | 1.4998 |
| 1.5086 | 3.84 | 804000 | 1.5001 |
| 1.5081 | 3.85 | 806000 | 1.5031 |
| 1.5097 | 3.86 | 808000 | 1.5008 |
| 1.5128 | 3.87 | 810000 | 1.4990 |
| 1.5093 | 3.88 | 812000 | 1.4994 |
| 1.5109 | 3.89 | 814000 | 1.5021 |
| 1.5049 | 3.9 | 816000 | 1.5012 |
| 1.5042 | 3.91 | 818000 | 1.5013 |
| 1.5053 | 3.92 | 820000 | 1.4946 |
| 1.5066 | 3.93 | 822000 | 1.4984 |
| 1.5074 | 3.93 | 824000 | 1.4963 |
| 1.5046 | 3.94 | 826000 | 1.4972 |
| 1.5043 | 3.95 | 828000 | 1.4970 |
| 1.5064 | 3.96 | 830000 | 1.4940 |
| 1.4999 | 3.97 | 832000 | 1.4940 |
| 1.5022 | 3.98 | 834000 | 1.4934 |
| 1.5054 | 3.99 | 836000 | 1.4929 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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