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whisper-small-ar-12hrsdarijadata-April21-params1
bouim/whisper-small-ar-12hrsdarijadata-April21-params1
whisper-small-ar-12hrsdarijadata-April21-params1 is a automatic speech recognition model from bouim. 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
- Apr 21, 2023
- Updated
- Apr 22, 2023
- SHA
- 2e16191b
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-small-ar-12hrsdarijadata-April21-params1
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6189
- Wer: 57.5010
- Cer: 22.7156
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-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.0603 | 0.38 | 250 | 0.8352 | 73.3652 | 36.2817 |
| 0.7041 | 0.75 | 500 | 0.6119 | 66.8656 | 29.7437 |
| 0.4434 | 1.13 | 750 | 0.5534 | 56.4001 | 24.9692 |
| 0.4344 | 1.51 | 1000 | 0.5341 | 55.8827 | 22.2788 |
| 0.3683 | 1.89 | 1250 | 0.5171 | 53.8931 | 23.3545 |
| 0.2964 | 2.26 | 1500 | 0.5245 | 53.2697 | 21.4447 |
| 0.2126 | 2.64 | 1750 | 0.5267 | 51.0545 | 19.9624 |
| 0.2095 | 3.02 | 2000 | 0.5428 | 55.1267 | 21.9697 |
| 0.1452 | 3.39 | 2250 | 0.5636 | 59.2386 | 23.4962 |
| 0.1123 | 3.77 | 2500 | 0.5598 | 54.0257 | 21.7816 |
| 0.077 | 4.15 | 2750 | 0.5809 | 53.5747 | 23.3614 |
| 0.0624 | 4.52 | 3000 | 0.5897 | 53.6941 | 22.1417 |
| 0.0492 | 4.9 | 3250 | 0.5973 | 54.0921 | 20.3922 |
| 0.0571 | 5.28 | 3500 | 0.6128 | 54.3043 | 21.2704 |
| 0.0637 | 5.66 | 3750 | 0.6139 | 54.6890 | 22.2114 |
| 0.0288 | 6.03 | 4000 | 0.6189 | 57.5010 | 22.7156 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.1.dev0
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Apr 21, 2023
- Updated
- Apr 22, 2023