🤗 HF Repo •🐱 Github Repo
Approximate Performance Evaluation
The following models are all trained and evaluated on a single RTX 3090 GPU.
Cantonese Test Results Comparison
MDCC
| Model name | Parameters | Finetune Steps | Time Spend | Training Loss | Validation Loss | CER % | Finetuned Model |
|---|---|---|---|---|---|---|---|
| whisper-tiny-cantonese | 39 M | 3200 | 4h 34m | 0.0485 | 0.771 | 11.10 | Link |
| whisper-base-cantonese | 74 M | 7200 | 13h 32m | 0.0186 | 0.477 | 7.66 | Link |
| whisper-small-cantonese | 244 M | 3600 | 6h 38m | 0.0266 | 0.137 | 6.16 | Link |
| whisper-small-lora-cantonese | 3.5 M | 8000 | 21h 27m | 0.0687 | 0.382 | 7.40 | Link |
| whisper-large-v2-lora-cantonese | 15 M | 10000 | 33h 40m | 0.0046 | 0.277 | 3.77 | Link |
Common Voice Corpus 11.0
| Model name | Original CER % | w/o Finetune CER % | Jointly Finetune CER % |
|---|---|---|---|
| whisper-tiny-cantonese | 124.03 | 66.85 | 35.87 |
| whisper-base-cantonese | 78.24 | 61.42 | 16.73 |
| whisper-small-cantonese | 52.83 | 31.23 | / |
| whisper-small-lora-cantonese | 37.53 | 19.38 | 14.73 |
| whisper-large-v2-lora-cantonese | 37.53 | 19.38 | 9.63 |
- Downloads last month
- 228
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.