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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-0front-1body-6rear
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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-0front-1body-6rear
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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: 0.4698
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- Wer: 0.1756
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- Mer: 0.1696
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- Wil: 0.2578
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- Wip: 0.7422
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- Hits: 55507
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- Substitutions: 6509
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- Deletions: 2571
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- Insertions: 2259
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- Cer: 0.1373
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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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| 0.6157 | 1.0 | 1457 | 0.4985 | 0.2141 | 0.2018 | 0.2933 | 0.7067 | 54712 | 6913 | 2962 | 3955 | 0.1920 |
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| 0.5098 | 2.0 | 2914 | 0.4500 | 0.1847 | 0.1781 | 0.2663 | 0.7337 | 55040 | 6505 | 3042 | 2383 | 0.1473 |
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| 0.4729 | 3.0 | 4371 | 0.4424 | 0.1768 | 0.1709 | 0.2591 | 0.7409 | 55397 | 6509 | 2681 | 2227 | 0.1386 |
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| 0.4284 | 4.0 | 5828 | 0.4473 | 0.1753 | 0.1696 | 0.2573 | 0.7427 | 55457 | 6461 | 2669 | 2194 | 0.1362 |
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| 0.394 | 5.0 | 7285 | 0.4462 | 0.1795 | 0.1729 | 0.2612 | 0.7388 | 55459 | 6530 | 2598 | 2468 | 0.1484 |
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| 0.3556 | 6.0 | 8742 | 0.4521 | 0.1759 | 0.1700 | 0.2579 | 0.7421 | 55449 | 6480 | 2658 | 2221 | 0.1365 |
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| 0.3348 | 7.0 | 10199 | 0.4588 | 0.1742 | 0.1686 | 0.2567 | 0.7433 | 55491 | 6491 | 2605 | 2156 | 0.1358 |
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| 0.3594 | 8.0 | 11656 | 0.4608 | 0.1755 | 0.1697 | 0.2580 | 0.7420 | 55468 | 6516 | 2603 | 2215 | 0.1371 |
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| 0.3065 | 9.0 | 13113 | 0.4685 | 0.1758 | 0.1698 | 0.2580 | 0.7420 | 55496 | 6510 | 2581 | 2263 | 0.1373 |
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| 0.2976 | 10.0 | 14570 | 0.4698 | 0.1756 | 0.1696 | 0.2578 | 0.7422 | 55507 | 6509 | 2571 | 2259 | 0.1373 |
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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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