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README.md
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This model is a fine-tuned version of [sonoisa/t5-base-japanese](https://huggingface.co/sonoisa/t5-base-japanese) on the te_dx_jp dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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- Mer: 0.1679
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- Wil: 0.
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- Wip: 0.
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- Hits:
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- Substitutions:
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- Deletions:
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- Insertions:
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- Cer: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer | Mer | Wil | Wip | Hits | Substitutions | Deletions | Insertions | Cer |
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### Framework versions
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This model is a fine-tuned version of [sonoisa/t5-base-japanese](https://huggingface.co/sonoisa/t5-base-japanese) on the te_dx_jp dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4589
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- Wer: 0.1739
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- Mer: 0.1679
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- Wil: 0.2545
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- Wip: 0.7455
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- Hits: 55667
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- Substitutions: 6385
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- Deletions: 2535
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- Insertions: 2309
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- Cer: 0.1363
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Wer | Mer | Wil | Wip | Hits | Substitutions | Deletions | Insertions | Cer |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:|
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| 0.6586 | 1.0 | 1457 | 0.4812 | 0.2110 | 0.1994 | 0.2888 | 0.7112 | 54745 | 6712 | 3130 | 3789 | 0.1784 |
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| 0.5246 | 2.0 | 2914 | 0.4383 | 0.1839 | 0.1770 | 0.2641 | 0.7359 | 55251 | 6428 | 2908 | 2544 | 0.1481 |
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| 0.4795 | 3.0 | 4371 | 0.4327 | 0.1811 | 0.1740 | 0.2610 | 0.7390 | 55523 | 6438 | 2626 | 2631 | 0.1458 |
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| 0.4224 | 4.0 | 5828 | 0.4328 | 0.1754 | 0.1693 | 0.2555 | 0.7445 | 55577 | 6338 | 2672 | 2318 | 0.1397 |
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| 0.3755 | 5.0 | 7285 | 0.4351 | 0.1723 | 0.1668 | 0.2529 | 0.7471 | 55607 | 6326 | 2654 | 2150 | 0.1362 |
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| 0.3538 | 6.0 | 8742 | 0.4413 | 0.1728 | 0.1670 | 0.2531 | 0.7469 | 55696 | 6341 | 2550 | 2271 | 0.1372 |
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| 0.3686 | 7.0 | 10199 | 0.4455 | 0.1715 | 0.1659 | 0.2519 | 0.7481 | 55692 | 6319 | 2576 | 2180 | 0.1354 |
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| 0.3004 | 8.0 | 11656 | 0.4518 | 0.1727 | 0.1668 | 0.2537 | 0.7463 | 55712 | 6400 | 2475 | 2281 | 0.1371 |
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| 0.2914 | 9.0 | 13113 | 0.4564 | 0.1739 | 0.1678 | 0.2544 | 0.7456 | 55681 | 6378 | 2528 | 2323 | 0.1370 |
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| 0.297 | 10.0 | 14570 | 0.4589 | 0.1739 | 0.1679 | 0.2545 | 0.7455 | 55667 | 6385 | 2535 | 2309 | 0.1363 |
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### Framework versions
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