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torgo_tiny_finetune_F01_frozen_encoder
jindaznb/torgo_tiny_finetune_F01_frozen_encoder
torgo_tiny_finetune_F01_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 13, 2024
- Updated
- Jun 13, 2024
- SHA
- 2c671541
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_F01_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: 0.2915
- Wer: 73.9389
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 |
|---|---|---|---|---|
| 0.7815 | 0.83 | 500 | 0.2625 | 39.3888 |
| 0.0936 | 1.66 | 1000 | 0.2655 | 29.4567 |
| 0.0711 | 2.49 | 1500 | 0.2517 | 25.4669 |
| 0.0456 | 3.32 | 2000 | 0.2738 | 28.6927 |
| 0.0327 | 4.15 | 2500 | 0.2770 | 34.8896 |
| 0.0258 | 4.98 | 3000 | 0.2653 | 20.0340 |
| 0.0181 | 5.8 | 3500 | 0.2902 | 27.0798 |
| 0.0145 | 6.63 | 4000 | 0.2801 | 22.3260 |
| 0.0114 | 7.46 | 4500 | 0.3174 | 27.0798 |
| 0.0094 | 8.29 | 5000 | 0.2789 | 47.8778 |
| 0.0072 | 9.12 | 5500 | 0.2827 | 20.7980 |
| 0.0058 | 9.95 | 6000 | 0.3011 | 23.8540 |
| 0.0046 | 10.78 | 6500 | 0.2892 | 23.0051 |
| 0.0035 | 11.61 | 7000 | 0.2858 | 20.5433 |
| 0.0034 | 12.44 | 7500 | 0.2876 | 25.2122 |
| 0.0021 | 13.27 | 8000 | 0.2876 | 23.1749 |
| 0.002 | 14.1 | 8500 | 0.3039 | 41.9355 |
| 0.0019 | 14.93 | 9000 | 0.3060 | 24.7029 |
| 0.001 | 15.75 | 9500 | 0.2938 | 30.4754 |
| 0.0009 | 16.58 | 10000 | 0.2998 | 31.3243 |
| 0.0007 | 17.41 | 10500 | 0.2933 | 37.0968 |
| 0.0005 | 18.24 | 11000 | 0.2937 | 39.7284 |
| 0.0004 | 19.07 | 11500 | 0.2921 | 69.8642 |
| 0.0002 | 19.9 | 12000 | 0.2915 | 73.9389 |
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 13, 2024
- Updated
- Jun 13, 2024