Downloads · 30 days
7
23% of all-time downloads
Wav2vec2-afr
Leonel-Maia/Wav2vec2-afr
Wav2vec2-afr is a automatic speech recognition model from Leonel-Maia. 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. --
All-time downloads
30
Public
Parameters
316M
25.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- May 12, 2025
- Updated
- May 13, 2025
- SHA
- 89768b56
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-afr
This model is a fine-tuned version of asr-africa/wav2vec2-xls-r-ewe-100-hours on the LEONEL-MAIA/EWE_DATASET_SPLITTED - DEFAULT dataset. It achieves the following results on the evaluation set:
- Loss: 0.1822
- Wer: 0.2055
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: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 60.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2638 | 0.3017 | 500 | 0.3208 | 0.3275 |
| 0.1603 | 0.6034 | 1000 | 0.2497 | 0.2649 |
| 0.142 | 0.9050 | 1500 | 0.2145 | 0.2488 |
| 0.1645 | 1.2064 | 2000 | 0.2023 | 0.2252 |
| 0.1818 | 1.5080 | 2500 | 0.1984 | 0.2177 |
| 0.1827 | 1.8097 | 3000 | 0.1995 | 0.2204 |
| 0.1859 | 2.1110 | 3500 | 0.1994 | 0.2240 |
| 0.2488 | 2.4127 | 4000 | 0.2040 | 0.2250 |
| 0.2292 | 2.7144 | 4500 | 0.1991 | 0.2260 |
| 0.2489 | 3.0157 | 5000 | 0.1845 | 0.2137 |
| 0.4731 | 3.3174 | 5500 | 0.1854 | 0.2121 |
| 0.2497 | 3.6191 | 6000 | 0.1888 | 0.2102 |
| 0.2872 | 3.9207 | 6500 | 0.1915 | 0.2197 |
| 0.248 | 4.2220 | 7000 | 0.1920 | 0.2199 |
| 0.2048 | 4.5237 | 7500 | 0.1822 | 0.2055 |
| 0.1977 | 4.8254 | 8000 | 0.1850 | 0.2094 |
| 0.1459 | 5.1267 | 8500 | 0.1905 | 0.2153 |
| 0.1471 | 5.4284 | 9000 | 0.1864 | 0.2023 |
| 0.1528 | 5.7301 | 9500 | 0.1829 | 0.2089 |
| 0.0668 | 6.0314 | 10000 | 0.1908 | 0.2050 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 12, 2025
- Updated
- May 13, 2025