Downloads · 30 days
4
24% of all-time downloads
torgo_tiny_finetune_M02
jindaznb/torgo_tiny_finetune_M02
torgo_tiny_finetune_M02 is a automatic speech recognition model from jindaznb. 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
17
Public
Repo size
302 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin151 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jun 9, 2024
- Updated
- Jun 9, 2024
- SHA
- 10453b96
Base models
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. -->
torgo_tiny_finetune_M02
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3391
- Wer: 30.4754
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: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6178 | 0.85 | 500 | 0.3570 | 29.2869 |
| 0.105 | 1.7 | 1000 | 0.3471 | 35.7385 |
| 0.1006 | 2.55 | 1500 | 0.3797 | 35.1443 |
| 0.0661 | 3.4 | 2000 | 0.3132 | 49.8302 |
| 0.0483 | 4.25 | 2500 | 0.3368 | 62.6486 |
| 0.0335 | 5.1 | 3000 | 0.2921 | 39.7284 |
| 0.0271 | 5.95 | 3500 | 0.3178 | 31.8336 |
| 0.0222 | 6.8 | 4000 | 0.3214 | 56.6214 |
| 0.0188 | 7.65 | 4500 | 0.3255 | 29.3718 |
| 0.0135 | 8.5 | 5000 | 0.3525 | 40.3226 |
| 0.0098 | 9.35 | 5500 | 0.3004 | 31.3243 |
| 0.0094 | 10.2 | 6000 | 0.3255 | 29.5416 |
| 0.0063 | 11.05 | 6500 | 0.3111 | 32.3430 |
| 0.0042 | 11.9 | 7000 | 0.3198 | 42.1053 |
| 0.0027 | 12.76 | 7500 | 0.2946 | 26.9100 |
| 0.0028 | 13.61 | 8000 | 0.3201 | 32.0034 |
| 0.0015 | 14.46 | 8500 | 0.3236 | 31.0696 |
| 0.0008 | 15.31 | 9000 | 0.3244 | 29.9660 |
| 0.0004 | 16.16 | 9500 | 0.3332 | 31.8336 |
| 0.0004 | 17.01 | 10000 | 0.3586 | 30.3905 |
| 0.0001 | 17.86 | 10500 | 0.3415 | 29.6265 |
| 0.0 | 18.71 | 11000 | 0.3403 | 29.7963 |
| 0.0001 | 19.56 | 11500 | 0.3391 | 30.4754 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jun 9, 2024
- Updated
- Jun 9, 2024