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TunLangModel1.0
Arbi-Houssem/TunLangModel1.0
TunLangModel1.0 is a automatic speech recognition model from Arbi-Houssem. 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 9, 2024
- Updated
- May 9, 2024
- SHA
- cddfbb09
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 Tunisien
This model is a fine-tuned version of openai/whisper-medium on the comondov dataset. It achieves the following results on the evaluation set:
- Loss: 1.7085
- Wer: 62.7119
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 |
|---|---|---|---|---|
| 0.1296 | 50.0 | 200 | 1.5371 | 63.0200 |
| 0.0012 | 100.0 | 400 | 1.6181 | 61.4792 |
| 0.0005 | 150.0 | 600 | 1.6781 | 63.3282 |
| 0.0004 | 200.0 | 800 | 1.7005 | 61.9414 |
| 0.0003 | 250.0 | 1000 | 1.7085 | 62.7119 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- ar
- Created
- May 9, 2024
- Updated
- May 9, 2024