metadata
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- te_dx_jp
model-index:
- name: t5-base-TEDxJP-4front-1body-4rear
results: []
t5-base-TEDxJP-4front-1body-4rear
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: 0.4419
- Wer: 0.1696
- Mer: 0.1638
- Wil: 0.2494
- Wip: 0.7506
- Hits: 55898
- Substitutions: 6290
- Deletions: 2399
- Insertions: 2262
- Cer: 0.1328
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.5923 | 1.0 | 1457 | 0.4757 | 0.2180 | 0.2043 | 0.2941 | 0.7059 | 54841 | 6796 | 2950 | 4332 | 0.1931 |
0.5311 | 2.0 | 2914 | 0.4278 | 0.1817 | 0.1745 | 0.2611 | 0.7389 | 55507 | 6397 | 2683 | 2656 | 0.1467 |
0.4511 | 3.0 | 4371 | 0.4187 | 0.1715 | 0.1659 | 0.2529 | 0.7471 | 55668 | 6395 | 2524 | 2157 | 0.1322 |
0.3544 | 4.0 | 5828 | 0.4179 | 0.1700 | 0.1644 | 0.2498 | 0.7502 | 55795 | 6272 | 2520 | 2185 | 0.1319 |
0.3649 | 5.0 | 7285 | 0.4210 | 0.1700 | 0.1645 | 0.2506 | 0.7494 | 55799 | 6334 | 2454 | 2195 | 0.1319 |
0.3622 | 6.0 | 8742 | 0.4223 | 0.1706 | 0.1649 | 0.2503 | 0.7497 | 55823 | 6278 | 2486 | 2256 | 0.1358 |
0.3286 | 7.0 | 10199 | 0.4258 | 0.1692 | 0.1638 | 0.2492 | 0.7508 | 55807 | 6273 | 2507 | 2149 | 0.1325 |
0.3069 | 8.0 | 11656 | 0.4307 | 0.1697 | 0.1640 | 0.2493 | 0.7507 | 55861 | 6265 | 2461 | 2232 | 0.1329 |
0.2776 | 9.0 | 13113 | 0.4403 | 0.1697 | 0.1640 | 0.2497 | 0.7503 | 55883 | 6304 | 2400 | 2257 | 0.1328 |
0.3175 | 10.0 | 14570 | 0.4419 | 0.1696 | 0.1638 | 0.2494 | 0.7506 | 55898 | 6290 | 2399 | 2262 | 0.1328 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1