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README.md
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---
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license: cc-by-sa-4.0
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tags:
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- generated_from_trainer
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datasets:
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- te_dx_jp
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model-index:
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- name: t5-base-TEDxJP-5front-1body-5rear
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# t5-base-TEDxJP-5front-1body-5rear
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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: 0.4393
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- Wer: 0.1715
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- Mer: 0.1657
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- Wil: 0.2520
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- Wip: 0.7480
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- Hits: 55766
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- Substitutions: 6346
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- Deletions: 2475
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- Insertions: 2256
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- Cer: 0.1352
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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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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| 0.5978 | 1.0 | 1457 | 0.4748 | 0.2133 | 0.2003 | 0.2897 | 0.7103 | 55011 | 6755 | 2821 | 4200 | 0.1826 |
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| 0.4837 | 2.0 | 2914 | 0.4190 | 0.1803 | 0.1737 | 0.2604 | 0.7396 | 55400 | 6393 | 2794 | 2459 | 0.1464 |
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| 0.4576 | 3.0 | 4371 | 0.4114 | 0.1729 | 0.1673 | 0.2547 | 0.7453 | 55606 | 6443 | 2538 | 2187 | 0.1342 |
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| 0.3888 | 4.0 | 5828 | 0.4169 | 0.1729 | 0.1671 | 0.2533 | 0.7467 | 55683 | 6347 | 2557 | 2264 | 0.1357 |
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| 0.3647 | 5.0 | 7285 | 0.4178 | 0.1728 | 0.1666 | 0.2528 | 0.7472 | 55832 | 6358 | 2397 | 2403 | 0.1364 |
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| 0.3226 | 6.0 | 8742 | 0.4199 | 0.1703 | 0.1648 | 0.2507 | 0.7493 | 55715 | 6304 | 2568 | 2125 | 0.1358 |
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| 0.3045 | 7.0 | 10199 | 0.4309 | 0.1711 | 0.1653 | 0.2513 | 0.7487 | 55793 | 6322 | 2472 | 2257 | 0.1360 |
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| 0.32 | 8.0 | 11656 | 0.4301 | 0.1714 | 0.1656 | 0.2518 | 0.7482 | 55768 | 6343 | 2476 | 2251 | 0.1341 |
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| 0.2809 | 9.0 | 13113 | 0.4371 | 0.1706 | 0.1649 | 0.2513 | 0.7487 | 55774 | 6355 | 2458 | 2203 | 0.1333 |
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| 0.2726 | 10.0 | 14570 | 0.4393 | 0.1715 | 0.1657 | 0.2520 | 0.7480 | 55766 | 6346 | 2475 | 2256 | 0.1352 |
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### Framework versions
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- Transformers 4.21.2
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- Pytorch 1.12.1+cu116
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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