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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-8front-1body-8rear |
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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-8front-1body-8rear |
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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: 0.4383 |
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- Wer: 0.1703 |
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- Mer: 0.1643 |
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- Wil: 0.2498 |
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- Wip: 0.7502 |
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- Hits: 55917 |
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- Substitutions: 6285 |
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- Deletions: 2385 |
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- Insertions: 2327 |
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- Cer: 0.1338 |
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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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| 0.5634 | 1.0 | 1457 | 0.4668 | 0.2271 | 0.2101 | 0.2986 | 0.7014 | 55139 | 6756 | 2692 | 5219 | 0.1993 | |
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| 0.5335 | 2.0 | 2914 | 0.4168 | 0.1852 | 0.1776 | 0.2649 | 0.7351 | 55407 | 6467 | 2713 | 2782 | 0.1495 | |
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| 0.4453 | 3.0 | 4371 | 0.4124 | 0.1738 | 0.1678 | 0.2545 | 0.7455 | 55683 | 6391 | 2513 | 2321 | 0.1344 | |
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| 0.388 | 4.0 | 5828 | 0.4082 | 0.1703 | 0.1646 | 0.2502 | 0.7498 | 55838 | 6297 | 2452 | 2249 | 0.1324 | |
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| 0.3448 | 5.0 | 7285 | 0.4156 | 0.1704 | 0.1646 | 0.2505 | 0.7495 | 55840 | 6320 | 2427 | 2257 | 0.1339 | |
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| 0.3103 | 6.0 | 8742 | 0.4177 | 0.1690 | 0.1632 | 0.2484 | 0.7516 | 55955 | 6263 | 2369 | 2280 | 0.1324 | |
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| 0.3369 | 7.0 | 10199 | 0.4225 | 0.1688 | 0.1631 | 0.2480 | 0.7520 | 55930 | 6230 | 2427 | 2244 | 0.1327 | |
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| 0.3127 | 8.0 | 11656 | 0.4294 | 0.1692 | 0.1636 | 0.2489 | 0.7511 | 55876 | 6265 | 2446 | 2220 | 0.1331 | |
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| 0.2739 | 9.0 | 13113 | 0.4329 | 0.1702 | 0.1643 | 0.2501 | 0.7499 | 55903 | 6316 | 2368 | 2307 | 0.1338 | |
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| 0.269 | 10.0 | 14570 | 0.4383 | 0.1703 | 0.1643 | 0.2498 | 0.7502 | 55917 | 6285 | 2385 | 2327 | 0.1338 | |
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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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