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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-7front-1body-7rear |
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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-7front-1body-7rear |
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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: 0.4385 |
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- Wer: 0.1688 |
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- Mer: 0.1632 |
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- Wil: 0.2486 |
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- Wip: 0.7514 |
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- Hits: 55895 |
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- Substitutions: 6273 |
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- Deletions: 2419 |
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- Insertions: 2208 |
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- Cer: 0.1334 |
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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: 10 |
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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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| 0.5657 | 1.0 | 1457 | 0.4744 | 0.2212 | 0.2056 | 0.2946 | 0.7054 | 55195 | 6783 | 2609 | 4892 | 0.1922 | |
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| 0.5388 | 2.0 | 2914 | 0.4193 | 0.1791 | 0.1724 | 0.2601 | 0.7399 | 55526 | 6485 | 2576 | 2507 | 0.1404 | |
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| 0.447 | 3.0 | 4371 | 0.4119 | 0.1728 | 0.1670 | 0.2531 | 0.7469 | 55690 | 6334 | 2563 | 2266 | 0.1341 | |
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| 0.3952 | 4.0 | 5828 | 0.4088 | 0.1704 | 0.1647 | 0.2503 | 0.7497 | 55802 | 6283 | 2502 | 2220 | 0.1330 | |
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| 0.3498 | 5.0 | 7285 | 0.4138 | 0.1701 | 0.1643 | 0.2500 | 0.7500 | 55881 | 6305 | 2401 | 2280 | 0.1321 | |
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| 0.3107 | 6.0 | 8742 | 0.4201 | 0.1693 | 0.1636 | 0.2497 | 0.7503 | 55888 | 6334 | 2365 | 2236 | 0.1319 | |
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| 0.3443 | 7.0 | 10199 | 0.4239 | 0.1694 | 0.1637 | 0.2495 | 0.7505 | 55890 | 6309 | 2388 | 2241 | 0.1328 | |
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| 0.3099 | 8.0 | 11656 | 0.4316 | 0.1695 | 0.1639 | 0.2496 | 0.7504 | 55833 | 6292 | 2462 | 2192 | 0.1337 | |
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| 0.2804 | 9.0 | 13113 | 0.4345 | 0.1687 | 0.1631 | 0.2486 | 0.7514 | 55896 | 6273 | 2418 | 2206 | 0.1332 | |
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| 0.2714 | 10.0 | 14570 | 0.4385 | 0.1688 | 0.1632 | 0.2486 | 0.7514 | 55895 | 6273 | 2419 | 2208 | 0.1334 | |
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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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