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whisper-large-cit-do1.5-wd1e-3
Makkoen/whisper-large-cit-do1.5-wd1e-3
whisper-large-cit-do1.5-wd1e-3 is a automatic speech recognition model from Makkoen. 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
- May 27, 2024
- Updated
- May 27, 2024
- SHA
- 1ecfc498
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. -->
whisper-large-cit-do1.5-wd1e-3
This model is a fine-tuned version of openai/whisper-large-v3 on the SF 200 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6797
- Wer: 33.6384
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: 1e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1289 | 0.8889 | 10 | 1.1191 | 48.9703 |
| 1.095 | 1.7778 | 20 | 1.0078 | 40.9611 |
| 0.936 | 2.6667 | 30 | 0.8691 | 39.3593 |
| 0.7555 | 3.5556 | 40 | 0.7930 | 33.6384 |
| 0.7013 | 4.4444 | 50 | 0.7202 | 34.7826 |
| 0.6006 | 5.3333 | 60 | 0.6553 | 32.4943 |
| 0.5082 | 6.2222 | 70 | 0.6172 | 31.5789 |
| 0.4133 | 7.1111 | 80 | 0.5908 | 33.4096 |
| 0.3771 | 8.0 | 90 | 0.5728 | 32.4943 |
| 0.3013 | 8.8889 | 100 | 0.5693 | 33.4096 |
| 0.266 | 9.7778 | 110 | 0.5728 | 33.4096 |
| 0.2148 | 10.6667 | 120 | 0.5830 | 32.2654 |
| 0.1829 | 11.5556 | 130 | 0.5947 | 32.7231 |
| 0.1531 | 12.4444 | 140 | 0.6069 | 31.3501 |
| 0.1246 | 13.3333 | 150 | 0.6206 | 34.0961 |
| 0.1186 | 14.2222 | 160 | 0.6353 | 33.1808 |
| 0.1013 | 15.1111 | 170 | 0.6533 | 35.0114 |
| 0.0869 | 16.0 | 180 | 0.6650 | 33.6384 |
| 0.0812 | 16.8889 | 190 | 0.6763 | 33.1808 |
| 0.0763 | 17.7778 | 200 | 0.6797 | 33.6384 |
Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- May 27, 2024
- Updated
- May 27, 2024