metadata
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-5front-1body-5rear
results: []
t5-base-TEDxJP-5front-1body-5rear
This model is a fine-tuned version of sonoisa/t5-base-japanese on the te_dx_jp dataset. It achieves the following results on the evaluation set:
- Loss: 0.4411
- Wer: 0.1694
- Mer: 0.1636
- Wil: 0.2489
- Wip: 0.7511
- Hits: 55916
- Substitutions: 6268
- Deletions: 2403
- Insertions: 2267
- Cer: 0.1371
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Mer | Wil | Wip | Hits | Substitutions | Deletions | Insertions | Cer |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.5975 | 1.0 | 1457 | 0.4673 | 0.2058 | 0.1947 | 0.2831 | 0.7169 | 54961 | 6617 | 3009 | 3665 | 0.1746 |
0.5623 | 2.0 | 2914 | 0.4246 | 0.1801 | 0.1737 | 0.2603 | 0.7397 | 55335 | 6381 | 2871 | 2378 | 0.1452 |
0.4438 | 3.0 | 4371 | 0.4104 | 0.1735 | 0.1675 | 0.2541 | 0.7459 | 55705 | 6379 | 2503 | 2326 | 0.1357 |
0.4177 | 4.0 | 5828 | 0.4119 | 0.1704 | 0.1647 | 0.2504 | 0.7496 | 55837 | 6299 | 2451 | 2258 | 0.1338 |
0.3548 | 5.0 | 7285 | 0.4171 | 0.1690 | 0.1637 | 0.2487 | 0.7513 | 55785 | 6228 | 2574 | 2115 | 0.1328 |
0.3115 | 6.0 | 8742 | 0.4245 | 0.1687 | 0.1633 | 0.2484 | 0.7516 | 55838 | 6243 | 2506 | 2148 | 0.1340 |
0.2997 | 7.0 | 10199 | 0.4302 | 0.1706 | 0.1647 | 0.2503 | 0.7497 | 55898 | 6300 | 2389 | 2329 | 0.1351 |
0.2977 | 8.0 | 11656 | 0.4361 | 0.1699 | 0.1642 | 0.2496 | 0.7504 | 55879 | 6278 | 2430 | 2266 | 0.1342 |
0.2639 | 9.0 | 13113 | 0.4393 | 0.1688 | 0.1632 | 0.2486 | 0.7514 | 55891 | 6265 | 2431 | 2208 | 0.1365 |
0.2879 | 10.0 | 14570 | 0.4411 | 0.1694 | 0.1636 | 0.2489 | 0.7511 | 55916 | 6268 | 2403 | 2267 | 0.1371 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1