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swahili_v2
etonkou/swahili_v2
swahili_v2 is a automatic speech recognition model from etonkou. 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
- Sep 30, 2023
- Updated
- Sep 30, 2023
- SHA
- e08eb284
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. -->
swahili_v2
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5957
- Wer: 0.4820
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: 0.0001
- train_batch_size: 3
- 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: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.0806 | 0.6 | 1000 | 1.2990 | 0.9279 |
| 1.3262 | 1.2 | 2000 | 0.9359 | 0.8004 |
| 1.0778 | 1.8 | 3000 | 1.0139 | 0.7421 |
| 0.9227 | 2.4 | 4000 | 0.7815 | 0.7053 |
| 0.8283 | 3.0 | 5000 | 0.6969 | 0.6340 |
| 0.683 | 3.6 | 6000 | 0.6665 | 0.6254 |
| 0.6208 | 4.2 | 7000 | 0.6304 | 0.5900 |
| 0.561 | 4.8 | 8000 | 0.5912 | 0.5748 |
| 0.4881 | 5.4 | 9000 | 0.5998 | 0.5523 |
| 0.474 | 6.0 | 10000 | 0.5488 | 0.5409 |
| 0.3989 | 6.6 | 11000 | 0.5550 | 0.5274 |
| 0.3581 | 7.2 | 12000 | 0.5702 | 0.5088 |
| 0.3348 | 7.8 | 13000 | 0.5739 | 0.5034 |
| 0.3059 | 8.4 | 14000 | 0.5915 | 0.5042 |
| 0.2765 | 9.0 | 15000 | 0.5720 | 0.4860 |
| 0.2489 | 9.6 | 16000 | 0.5957 | 0.4820 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Sep 30, 2023
- Updated
- Sep 30, 2023