|
--- |
|
license: cc-by-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- te_dx_jp |
|
model-index: |
|
- name: t5-base-TEDxJP-0front-1body-10rear-order-RB |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# t5-base-TEDxJP-0front-1body-10rear-order-RB |
|
|
|
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. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4713 |
|
- Wer: 0.1763 |
|
- Mer: 0.1704 |
|
- Wil: 0.2586 |
|
- Wip: 0.7414 |
|
- Hits: 55456 |
|
- Substitutions: 6510 |
|
- Deletions: 2621 |
|
- Insertions: 2256 |
|
- Cer: 0.1383 |
|
|
|
## 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: 0 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:-----:|:-------------:|:---------:|:----------:|:------:| |
|
| 0.6725 | 1.0 | 1457 | 0.4909 | 0.2293 | 0.2133 | 0.3017 | 0.6983 | 54628 | 6686 | 3273 | 4851 | 0.2018 | |
|
| 0.5083 | 2.0 | 2914 | 0.4537 | 0.1849 | 0.1781 | 0.2663 | 0.7337 | 55108 | 6513 | 2966 | 2464 | 0.1465 | |
|
| 0.4943 | 3.0 | 4371 | 0.4466 | 0.1778 | 0.1716 | 0.2599 | 0.7401 | 55424 | 6519 | 2644 | 2319 | 0.1377 | |
|
| 0.4454 | 4.0 | 5828 | 0.4385 | 0.1760 | 0.1703 | 0.2579 | 0.7421 | 55384 | 6452 | 2751 | 2163 | 0.1380 | |
|
| 0.411 | 5.0 | 7285 | 0.4460 | 0.1755 | 0.1697 | 0.2570 | 0.7430 | 55466 | 6430 | 2691 | 2216 | 0.1379 | |
|
| 0.3756 | 6.0 | 8742 | 0.4519 | 0.1750 | 0.1694 | 0.2568 | 0.7432 | 55419 | 6435 | 2733 | 2133 | 0.1383 | |
|
| 0.3647 | 7.0 | 10199 | 0.4585 | 0.1755 | 0.1699 | 0.2579 | 0.7421 | 55368 | 6475 | 2744 | 2115 | 0.1379 | |
|
| 0.3079 | 8.0 | 11656 | 0.4622 | 0.1763 | 0.1704 | 0.2590 | 0.7410 | 55416 | 6540 | 2631 | 2213 | 0.1387 | |
|
| 0.3029 | 9.0 | 13113 | 0.4699 | 0.1762 | 0.1703 | 0.2584 | 0.7416 | 55451 | 6499 | 2637 | 2245 | 0.1386 | |
|
| 0.2968 | 10.0 | 14570 | 0.4713 | 0.1763 | 0.1704 | 0.2586 | 0.7414 | 55456 | 6510 | 2621 | 2256 | 0.1383 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.2 |
|
- Pytorch 1.12.1+cu116 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
