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torgo_tiny_finetune_M02_frozen_encoder
jindaznb/torgo_tiny_finetune_M02_frozen_encoder
torgo_tiny_finetune_M02_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
- 629074ec
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_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: 0.2969
- Wer: 44.9915
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 |
|---|---|---|---|---|
| 0.7661 | 0.85 | 500 | 0.2672 | 64.6859 |
| 0.0893 | 1.7 | 1000 | 0.2523 | 24.2784 |
| 0.0664 | 2.55 | 1500 | 0.2562 | 20.3735 |
| 0.0439 | 3.4 | 2000 | 0.2674 | 98.8115 |
| 0.0303 | 4.25 | 2500 | 0.2566 | 22.1562 |
| 0.0224 | 5.1 | 3000 | 0.2737 | 24.7878 |
| 0.0164 | 5.95 | 3500 | 0.2761 | 41.3413 |
| 0.0139 | 6.8 | 4000 | 0.2923 | 31.3243 |
| 0.0102 | 7.65 | 4500 | 0.2841 | 45.5008 |
| 0.0082 | 8.5 | 5000 | 0.2913 | 36.5874 |
| 0.0058 | 9.35 | 5500 | 0.3038 | 22.2411 |
| 0.0065 | 10.2 | 6000 | 0.2853 | 22.6655 |
| 0.0052 | 11.05 | 6500 | 0.2806 | 22.4958 |
| 0.0033 | 11.9 | 7000 | 0.2866 | 30.8149 |
| 0.0026 | 12.76 | 7500 | 0.2852 | 24.3633 |
| 0.0027 | 13.61 | 8000 | 0.2956 | 54.4992 |
| 0.0017 | 14.46 | 8500 | 0.2959 | 31.0696 |
| 0.0012 | 15.31 | 9000 | 0.2974 | 35.9932 |
| 0.0012 | 16.16 | 9500 | 0.2993 | 39.5586 |
| 0.0008 | 17.01 | 10000 | 0.2950 | 44.1426 |
| 0.0004 | 17.86 | 10500 | 0.2988 | 47.0289 |
| 0.0002 | 18.71 | 11000 | 0.2948 | 44.2275 |
| 0.0002 | 19.56 | 11500 | 0.2969 | 44.9915 |
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