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wav2vec2-large-xls-r-may23-luganda-colab
Gemmar/wav2vec2-large-xls-r-may23-luganda-colab
wav2vec2-large-xls-r-may23-luganda-colab is a automatic speech recognition model from Gemmar. 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
- May 23, 2023
- Updated
- Jun 23, 2023
- SHA
- a81b6437
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. -->
wav2vec2-large-xls-r-may23-luganda-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.7210
- Wer: 0.5021
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0539 | 7.77 | 400 | 0.6641 | 0.5738 |
| 0.0725 | 15.53 | 800 | 0.6735 | 0.5932 |
| 0.058 | 23.3 | 1200 | 0.6754 | 0.5751 |
| 0.0517 | 31.07 | 1600 | 0.6591 | 0.5901 |
| 0.0437 | 38.83 | 2000 | 0.7140 | 0.5658 |
| 0.0366 | 46.6 | 2400 | 0.7154 | 0.5602 |
| 0.0295 | 54.37 | 2800 | 0.6942 | 0.5140 |
| 0.0251 | 62.14 | 3200 | 0.7095 | 0.5204 |
| 0.0191 | 69.9 | 3600 | 0.7459 | 0.5267 |
| 0.0157 | 77.67 | 4000 | 0.6825 | 0.5155 |
| 0.0126 | 85.44 | 4400 | 0.7197 | 0.5135 |
| 0.0098 | 93.2 | 4800 | 0.7210 | 0.5021 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 23, 2023
- Updated
- Jun 23, 2023