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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: 0.4384 |
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- Wer: 0.1692 |
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- Mer: 0.1635 |
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- Wil: 0.2483 |
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- Wip: 0.7517 |
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- Hits: 55908 |
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- Substitutions: 6222 |
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- Deletions: 2457 |
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- Insertions: 2249 |
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- Cer: 0.1327 |
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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: 30 |
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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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| 0.5881 | 1.0 | 1457 | 0.4572 | 0.2115 | 0.1995 | 0.2882 | 0.7118 | 54840 | 6661 | 3086 | 3916 | 0.1812 | |
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| 0.5018 | 2.0 | 2914 | 0.4167 | 0.1843 | 0.1765 | 0.2640 | 0.7360 | 55546 | 6494 | 2547 | 2863 | 0.1490 | |
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| 0.4633 | 3.0 | 4371 | 0.4110 | 0.1738 | 0.1679 | 0.2540 | 0.7460 | 55623 | 6327 | 2637 | 2260 | 0.1369 | |
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| 0.3971 | 4.0 | 5828 | 0.4068 | 0.1724 | 0.1666 | 0.2522 | 0.7478 | 55672 | 6278 | 2637 | 2218 | 0.1351 | |
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| 0.3907 | 5.0 | 7285 | 0.4131 | 0.1688 | 0.1635 | 0.2479 | 0.7521 | 55789 | 6180 | 2618 | 2106 | 0.1325 | |
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| 0.3305 | 6.0 | 8742 | 0.4147 | 0.1706 | 0.1649 | 0.2504 | 0.7496 | 55797 | 6281 | 2509 | 2227 | 0.1336 | |
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| 0.2937 | 7.0 | 10199 | 0.4236 | 0.1692 | 0.1636 | 0.2482 | 0.7518 | 55883 | 6207 | 2497 | 2223 | 0.1334 | |
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| 0.2649 | 8.0 | 11656 | 0.4307 | 0.1693 | 0.1638 | 0.2493 | 0.7507 | 55806 | 6272 | 2509 | 2154 | 0.1329 | |
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| 0.2914 | 9.0 | 13113 | 0.4319 | 0.1691 | 0.1634 | 0.2482 | 0.7518 | 55928 | 6230 | 2429 | 2262 | 0.1328 | |
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| 0.2598 | 10.0 | 14570 | 0.4384 | 0.1692 | 0.1635 | 0.2483 | 0.7517 | 55908 | 6222 | 2457 | 2249 | 0.1327 | |
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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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