Downloads · 30 days
12
4% of all-time downloads
whisper-small-ja
toshiouchiyama/whisper-small-ja
whisper-small-ja is a automatic speech recognition model from toshiouchiyama. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
339
Public
Repo size
14.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin967 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jan 2, 2023
- Updated
- Jan 31, 2023
- SHA
- a4959838
Model card
From the Hugging Face model README
<!-- 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. -->
whisper-small-ja
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3967
- Wer: 18.3755
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.3 | 10 | 1.1627 | 26.0985 |
| No log | 0.61 | 20 | 0.7416 | 900.3995 |
| 1.2431 | 0.91 | 30 | 0.6344 | 60.3196 |
| 1.2431 | 1.21 | 40 | 0.5944 | 20.2397 |
| 0.5462 | 1.52 | 50 | 0.5341 | 19.3076 |
| 0.5462 | 1.82 | 60 | 0.4953 | 18.5087 |
| 0.5462 | 2.12 | 70 | 0.4715 | 19.9734 |
| 0.3259 | 2.42 | 80 | 0.4469 | 18.2423 |
| 0.3259 | 2.73 | 90 | 0.4246 | 19.7071 |
| 0.1986 | 3.03 | 100 | 0.4076 | 19.0413 |
| 0.1986 | 3.33 | 110 | 0.3949 | 17.7097 |
| 0.1986 | 3.64 | 120 | 0.4008 | 20.5060 |
| 0.1101 | 3.94 | 130 | 0.3892 | 18.3755 |
| 0.1101 | 4.24 | 140 | 0.3873 | 18.3755 |
| 0.0695 | 4.55 | 150 | 0.3930 | 19.7071 |
| 0.0695 | 4.85 | 160 | 0.3857 | 18.1092 |
| 0.0695 | 5.15 | 170 | 0.3861 | 19.0413 |
| 0.0467 | 5.45 | 180 | 0.3913 | 18.5087 |
| 0.0467 | 5.76 | 190 | 0.3963 | 18.7750 |
| 0.0346 | 6.06 | 200 | 0.3967 | 18.3755 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ja
- Created
- Jan 2, 2023
- Updated
- Jan 31, 2023