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w2v-bert-2.0-armenian-speech-model-CV16
GoshKolotyan/w2v-bert-2.0-armenian-speech-model-CV16
w2v-bert-2.0-armenian-speech-model-CV16 is a automatic speech recognition model from GoshKolotyan. 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 11, 2025
- Updated
- Jun 11, 2025
- SHA
- 46d7a610
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. -->
w2v-bert-2.0-armenian-speech-model-CV16
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1620
- Wer: 0.1351
- Cer: 0.0234
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.3609 | 1.5973 | 300 | 0.1979 | 0.2548 | 0.0429 |
| 0.1429 | 3.192 | 600 | 0.1795 | 0.1918 | 0.0336 |
| 0.0862 | 4.7893 | 900 | 0.1608 | 0.1696 | 0.0293 |
| 0.0479 | 6.384 | 1200 | 0.1459 | 0.1450 | 0.0251 |
| 0.0243 | 7.9813 | 1500 | 0.1534 | 0.1387 | 0.0239 |
| 0.0105 | 9.576 | 1800 | 0.1620 | 0.1351 | 0.0234 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Jun 11, 2025
- Updated
- Jun 11, 2025