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torgo_tiny_finetune_M01_frozen_encoder
jindaznb/torgo_tiny_finetune_M01_frozen_encoder
torgo_tiny_finetune_M01_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
- b9bebcd4
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_M01_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: 0.2864
- Wer: 45.6706
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 |
|---|---|---|---|---|
| 0.768 | 0.85 | 500 | 0.2601 | 25.8913 |
| 0.0914 | 1.7 | 1000 | 0.2569 | 99.8302 |
| 0.0699 | 2.55 | 1500 | 0.2626 | 39.3039 |
| 0.042 | 3.4 | 2000 | 0.2691 | 26.0611 |
| 0.0336 | 4.24 | 2500 | 0.2619 | 25.4669 |
| 0.0229 | 5.09 | 3000 | 0.2613 | 29.2020 |
| 0.0166 | 5.94 | 3500 | 0.2525 | 30.0509 |
| 0.0112 | 6.79 | 4000 | 0.2843 | 30.7301 |
| 0.0113 | 7.64 | 4500 | 0.2862 | 25.8913 |
| 0.0085 | 8.49 | 5000 | 0.2726 | 29.5416 |
| 0.0059 | 9.34 | 5500 | 0.2782 | 35.6537 |
| 0.0052 | 10.19 | 6000 | 0.2971 | 39.6435 |
| 0.0041 | 11.04 | 6500 | 0.2886 | 26.9949 |
| 0.0043 | 11.88 | 7000 | 0.2952 | 29.2869 |
| 0.0031 | 12.73 | 7500 | 0.2858 | 34.3803 |
| 0.0022 | 13.58 | 8000 | 0.2844 | 35.9083 |
| 0.0019 | 14.43 | 8500 | 0.2749 | 33.7861 |
| 0.0013 | 15.28 | 9000 | 0.2882 | 41.3413 |
| 0.0014 | 16.13 | 9500 | 0.2817 | 44.3973 |
| 0.0008 | 16.98 | 10000 | 0.2872 | 39.7284 |
| 0.0006 | 17.83 | 10500 | 0.2846 | 41.8506 |
| 0.0003 | 18.68 | 11000 | 0.2900 | 45.2462 |
| 0.0003 | 19.52 | 11500 | 0.2864 | 45.6706 |
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