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whisper-tiny-all-audios
breco/whisper-tiny-all-audios
whisper-tiny-all-audios is a automatic speech recognition model from breco. 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
- Sep 6, 2024
- Updated
- Sep 7, 2024
- SHA
- 4f3c7fcb
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 Tiny All Audios - vfranchis
This model is a fine-tuned version of openai/whisper-tiny on the All audios 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0368
- Wer: 1.9658
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 25
- training_steps: 650
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4661 | 0.05 | 25 | 0.5654 | 20.5212 |
| 0.2642 | 0.1 | 50 | 0.1588 | 8.6859 |
| 0.1282 | 0.15 | 75 | 0.1102 | 6.3494 |
| 0.0861 | 0.2 | 100 | 0.0901 | 4.9068 |
| 0.0652 | 0.25 | 125 | 0.0784 | 4.0738 |
| 0.0676 | 0.3 | 150 | 0.0695 | 3.4490 |
| 0.0865 | 0.35 | 175 | 0.0649 | 3.4185 |
| 0.0454 | 0.4 | 200 | 0.0610 | 3.0477 |
| 0.0517 | 0.45 | 225 | 0.0567 | 2.9664 |
| 0.0471 | 0.5 | 250 | 0.0548 | 2.8344 |
| 0.0394 | 0.55 | 275 | 0.0521 | 2.8648 |
| 0.0347 | 0.6 | 300 | 0.0488 | 2.4585 |
| 0.0596 | 0.65 | 325 | 0.0477 | 2.4483 |
| 0.0426 | 0.7 | 350 | 0.0452 | 2.7836 |
| 0.0428 | 0.75 | 375 | 0.0436 | 2.2401 |
| 0.0518 | 0.8 | 400 | 0.0417 | 2.1181 |
| 0.0379 | 0.85 | 425 | 0.0407 | 2.0928 |
| 0.0259 | 0.9 | 450 | 0.0399 | 1.9861 |
| 0.0691 | 0.95 | 475 | 0.0394 | 2.2096 |
| 0.0382 | 1.0 | 500 | 0.0384 | 2.1131 |
| 0.0311 | 1.05 | 525 | 0.0377 | 1.9810 |
| 0.0301 | 1.1 | 550 | 0.0375 | 1.9404 |
| 0.021 | 1.15 | 575 | 0.0371 | 1.9505 |
| 0.0205 | 1.2 | 600 | 0.0369 | 1.9404 |
| 0.0163 | 1.25 | 625 | 0.0369 | 1.9505 |
| 0.018 | 1.3 | 650 | 0.0368 | 1.9658 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- spa
- Created
- Sep 6, 2024
- Updated
- Sep 7, 2024