Downloads · 30 days
8
25% of all-time downloads
whisper-tiny-en-US
taohoang/whisper-tiny-en-US
whisper-tiny-en-US is a automatic speech recognition model from taohoang. 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
32
Public
Repo size
2.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin151 MB · 99%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Aug 5, 2023
- Updated
- Aug 5, 2023
- SHA
- 1d92d23b
Base models
Datasets
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-tiny-en-US
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6286
- Wer Ortho: 0.3430
- Wer: 0.3436
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: 5e-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: constant_with_warmup
- lr_scheduler_warmup_steps: 10
- training_steps: 225
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 3.2798 | 0.25 | 14 | 0.9783 | 0.7218 | 0.6889 |
| 0.6283 | 0.5 | 28 | 0.5667 | 0.4479 | 0.4427 |
| 0.5574 | 0.75 | 42 | 0.5307 | 0.4812 | 0.4858 |
| 0.501 | 1.0 | 56 | 0.5130 | 0.3800 | 0.3813 |
| 0.2296 | 1.25 | 70 | 0.5057 | 0.3479 | 0.3436 |
| 0.2296 | 1.5 | 84 | 0.5515 | 0.3572 | 0.3512 |
| 0.2207 | 1.75 | 98 | 0.5356 | 0.3578 | 0.3530 |
| 0.1928 | 2.0 | 112 | 0.5288 | 0.3226 | 0.3200 |
| 0.0795 | 2.25 | 126 | 0.5532 | 0.3257 | 0.3259 |
| 0.0651 | 2.5 | 140 | 0.5833 | 0.3504 | 0.3512 |
| 0.0719 | 2.75 | 154 | 0.5931 | 0.3467 | 0.3501 |
| 0.0722 | 3.0 | 168 | 0.5994 | 0.3498 | 0.3477 |
| 0.0231 | 3.25 | 182 | 0.6030 | 0.3270 | 0.3264 |
| 0.0433 | 3.5 | 196 | 0.6059 | 0.3214 | 0.3200 |
| 0.0663 | 3.75 | 210 | 0.6262 | 0.3646 | 0.3648 |
| 0.0396 | 4.0 | 224 | 0.6286 | 0.3430 | 0.3436 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Aug 5, 2023
- Updated
- Aug 5, 2023