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torgo_tiny_finetune_M05
jindaznb/torgo_tiny_finetune_M05
torgo_tiny_finetune_M05 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. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jun 11, 2024
- Updated
- Jun 11, 2024
- SHA
- 5d4770db
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_M05
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: 0.3072
- Wer: 24.1935
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 |
|---|---|---|---|---|
| 0.6262 | 0.84 | 500 | 0.3083 | 50.8489 |
| 0.1041 | 1.68 | 1000 | 0.3578 | 41.3413 |
| 0.0997 | 2.53 | 1500 | 0.3539 | 51.6978 |
| 0.0694 | 3.37 | 2000 | 0.3092 | 83.9559 |
| 0.0489 | 4.21 | 2500 | 0.3775 | 64.3463 |
| 0.0382 | 5.05 | 3000 | 0.3589 | 67.7419 |
| 0.0268 | 5.89 | 3500 | 0.3005 | 29.7114 |
| 0.0209 | 6.73 | 4000 | 0.3221 | 21.5620 |
| 0.0173 | 7.58 | 4500 | 0.3337 | 42.9542 |
| 0.0128 | 8.42 | 5000 | 0.3374 | 27.0798 |
| 0.011 | 9.26 | 5500 | 0.3639 | 20.7131 |
| 0.0083 | 10.1 | 6000 | 0.3622 | 24.9576 |
| 0.0066 | 10.94 | 6500 | 0.2958 | 21.5620 |
| 0.005 | 11.78 | 7000 | 0.3478 | 46.4346 |
| 0.0023 | 12.63 | 7500 | 0.3206 | 33.1919 |
| 0.0026 | 13.47 | 8000 | 0.3023 | 27.8438 |
| 0.0017 | 14.31 | 8500 | 0.2990 | 19.9491 |
| 0.0008 | 15.15 | 9000 | 0.2862 | 17.6570 |
| 0.0007 | 15.99 | 9500 | 0.2924 | 20.5433 |
| 0.0002 | 16.84 | 10000 | 0.2935 | 23.1749 |
| 0.0001 | 17.68 | 10500 | 0.3048 | 23.5993 |
| 0.0001 | 18.52 | 11000 | 0.3061 | 24.5331 |
| 0.0001 | 19.36 | 11500 | 0.3072 | 24.1935 |
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 11, 2024
- Updated
- Jun 11, 2024