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wav2vec2-bert-fon
Zelyanoth/wav2vec2-bert-fon
wav2vec2-bert-fon is a automatic speech recognition model from Zelyanoth. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Jun 19, 2024
- Updated
- Jun 21, 2024
- SHA
- 07d2f5a3
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. -->
wav2vec2-bert-fon
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.1612
- Wer: 0.1324
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.18 | 250 | 1.2212 | 0.8079 |
| 2.1756 | 0.35 | 500 | 0.6697 | 0.6058 |
| 2.1756 | 0.53 | 750 | 0.5137 | 0.4606 |
| 0.5041 | 0.7 | 1000 | 0.4337 | 0.4234 |
| 0.5041 | 0.88 | 1250 | 0.3452 | 0.3529 |
| 0.426 | 1.05 | 1500 | 0.2770 | 0.2910 |
| 0.426 | 1.23 | 1750 | 0.2681 | 0.2439 |
| 0.2916 | 1.4 | 2000 | 0.2423 | 0.2155 |
| 0.2916 | 1.58 | 2250 | 0.2342 | 0.2077 |
| 0.2591 | 1.75 | 2500 | 0.1986 | 0.1791 |
| 0.2591 | 1.93 | 2750 | 0.1864 | 0.1597 |
| 0.2261 | 2.1 | 3000 | 0.1712 | 0.1419 |
| 0.2261 | 2.28 | 3250 | 0.1786 | 0.1497 |
| 0.1564 | 2.45 | 3500 | 0.1612 | 0.1324 |
| 0.1564 | 2.63 | 3750 | 0.1730 | 0.1591 |
| 0.1542 | 2.8 | 4000 | 0.1558 | 0.1364 |
| 0.1542 | 2.98 | 4250 | 0.1493 | 0.1581 |
| 0.1559 | 3.15 | 4500 | 0.1489 | 0.1347 |
| 0.1559 | 3.33 | 4750 | 0.2036 | 0.1486 |
| 0.1992 | 3.5 | 5000 | 0.2644 | 0.1582 |
| 0.1992 | 3.68 | 5250 | 0.2401 | 0.1878 |
| 0.291 | 3.85 | 5500 | 0.2409 | 0.1749 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Jun 19, 2024
- Updated
- Jun 21, 2024