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wav2vec2-large-xls-r-darija-colab
khaoulaoub/wav2vec2-large-xls-r-darija-colab
wav2vec2-large-xls-r-darija-colab is a automatic speech recognition model from khaoulaoub. 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
- wav2vec2
- Access
- Public
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023
- SHA
- cb76af41
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. -->
wav2vec2-large-xls-r-darija-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4380
- Wer: 0.3190
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.024 | 5.18 | 400 | 0.4523 | 0.5311 |
| 0.3011 | 10.36 | 800 | 0.3492 | 0.3792 |
| 0.1199 | 15.53 | 1200 | 0.3939 | 0.3499 |
| 0.0661 | 20.71 | 1600 | 0.4154 | 0.3309 |
| 0.0471 | 25.89 | 2000 | 0.4380 | 0.3190 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023