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torgo_tiny_finetune_M05_frozen_encoder
jindaznb/torgo_tiny_finetune_M05_frozen_encoder
torgo_tiny_finetune_M05_frozen_encoder 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 12, 2024
- Updated
- Jun 12, 2024
- SHA
- 7e0c9ed5
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_frozen_encoder
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: 0.2755
- Wer: 40.5772
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 |
|---|---|---|---|---|
| 0.7762 | 0.84 | 500 | 0.2681 | 42.3599 |
| 0.0927 | 1.68 | 1000 | 0.2688 | 26.0611 |
| 0.0703 | 2.53 | 1500 | 0.2827 | 27.6740 |
| 0.0457 | 3.37 | 2000 | 0.2467 | 22.4109 |
| 0.0318 | 4.21 | 2500 | 0.2900 | 21.8166 |
| 0.0225 | 5.05 | 3000 | 0.2947 | 23.9389 |
| 0.0173 | 5.89 | 3500 | 0.2752 | 22.3260 |
| 0.0127 | 6.73 | 4000 | 0.2749 | 22.7504 |
| 0.0112 | 7.58 | 4500 | 0.2957 | 22.4109 |
| 0.008 | 8.42 | 5000 | 0.2765 | 23.3447 |
| 0.0071 | 9.26 | 5500 | 0.2780 | 30.3056 |
| 0.0049 | 10.1 | 6000 | 0.2827 | 23.5144 |
| 0.0045 | 10.94 | 6500 | 0.2884 | 34.5501 |
| 0.0036 | 11.78 | 7000 | 0.2605 | 36.1630 |
| 0.0028 | 12.63 | 7500 | 0.2787 | 30.5603 |
| 0.0024 | 13.47 | 8000 | 0.2758 | 31.5789 |
| 0.0016 | 14.31 | 8500 | 0.2801 | 33.1919 |
| 0.0018 | 15.15 | 9000 | 0.2779 | 33.9559 |
| 0.0011 | 15.99 | 9500 | 0.2737 | 37.2666 |
| 0.0008 | 16.84 | 10000 | 0.2757 | 31.5789 |
| 0.0005 | 17.68 | 10500 | 0.2787 | 35.6537 |
| 0.0004 | 18.52 | 11000 | 0.2747 | 35.9083 |
| 0.0003 | 19.36 | 11500 | 0.2755 | 40.5772 |
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 12, 2024
- Updated
- Jun 12, 2024