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whisper-tiny-es
ctam8736/whisper-tiny-es
whisper-tiny-es is a automatic speech recognition model from ctam8736. 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
- Dec 13, 2023
- Updated
- Dec 15, 2023
- SHA
- 7681dfe0
Base models
Datasets
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 Papi/Es
This model is a fine-tuned version of openai/whisper-tiny on the Papi ASR Test dataset. It achieves the following results on the evaluation set:
- Loss: 0.1243
- Wer: 29.9772
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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0881 | 0.34 | 200 | 0.1414 | 23.3066 |
| 0.0563 | 0.69 | 400 | 0.1388 | 23.8738 |
| 0.0416 | 1.03 | 600 | 0.1367 | 26.2630 |
| 0.044 | 1.38 | 800 | 0.1295 | 29.1289 |
| 0.0546 | 1.72 | 1000 | 0.1243 | 29.9772 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- es
- Created
- Dec 13, 2023
- Updated
- Dec 15, 2023