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whisper-large-v3-pl-finetuned
liqi03/whisper-large-v3-pl-finetuned
whisper-large-v3-pl-finetuned is a automatic speech recognition model from liqi03. 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
- Jul 23, 2024
- Updated
- Jul 24, 2024
- SHA
- 2e0968d9
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 V3 pl - Chee Li
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1865
- Wer: 614.9727
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1328 | 0.6439 | 1000 | 0.2206 | 275.0400 |
| 0.0517 | 1.2878 | 2000 | 0.2183 | 668.6775 |
| 0.0501 | 1.9317 | 3000 | 0.1740 | 468.4439 |
| 0.022 | 2.5757 | 4000 | 0.1865 | 614.9727 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- pl
- Created
- Jul 23, 2024
- Updated
- Jul 24, 2024