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wav2vec2-common_voice-tr-demo
ylacombe/wav2vec2-common_voice-tr-demo
wav2vec2-common_voice-tr-demo is a automatic speech recognition model from ylacombe. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Jan 1, 2024
- Updated
- Jan 15, 2024
- SHA
- 3723049b
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-common_voice-tr-demo
This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - TR dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
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: 0.007448827845832091
- train_batch_size: 20
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 15.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.27 | 300 | 3.2930 | 1.0 |
| 5.6462 | 0.55 | 600 | 3.4159 | 1.0 |
| 5.6462 | 0.82 | 900 | 3.4422 | 1.0 |
| 3.3522 | 1.1 | 1200 | 3.3719 | 1.0 |
| 3.2605 | 1.37 | 1500 | 3.4026 | 1.0 |
| 3.2605 | 1.64 | 1800 | 3.4448 | 1.0 |
| 3.2766 | 1.92 | 2100 | 3.4736 | 0.9999 |
| 3.2766 | 2.19 | 2400 | 3.9828 | 1.0 |
| 3.2853 | 2.47 | 2700 | 3.5532 | 1.0 |
| 3.3389 | 2.74 | 3000 | 3.7819 | 1.0 |
| 3.3389 | 3.01 | 3300 | 3.2250 | 1.0 |
| 3.2186 | 3.29 | 3600 | 3.2373 | 1.0 |
| 3.2186 | 3.56 | 3900 | 3.2162 | 1.0 |
| 3.1916 | 3.84 | 4200 | 3.2368 | 1.0 |
| 3.2188 | 4.11 | 4500 | 3.2377 | 1.0 |
| 3.2188 | 4.38 | 4800 | 3.4207 | 1.0 |
| 5.3067 | 4.66 | 5100 | nan | 1.0 |
| 5.3067 | 4.93 | 5400 | nan | 1.0 |
| 0.0 | 5.21 | 5700 | nan | 1.0 |
| 0.0 | 5.48 | 6000 | nan | 1.0 |
| 0.0 | 5.75 | 6300 | nan | 1.0 |
| 0.0 | 6.03 | 6600 | nan | 1.0 |
| 0.0 | 6.3 | 6900 | nan | 1.0 |
| 0.0 | 6.58 | 7200 | nan | 1.0 |
| 0.0 | 6.85 | 7500 | nan | 1.0 |
| 0.0 | 7.12 | 7800 | nan | 1.0 |
| 0.0 | 7.4 | 8100 | nan | 1.0 |
| 0.0 | 7.67 | 8400 | nan | 1.0 |
| 0.0 | 7.95 | 8700 | nan | 1.0 |
| 0.0 | 8.22 | 9000 | nan | 1.0 |
| 0.0 | 8.49 | 9300 | nan | 1.0 |
| 0.0 | 8.77 | 9600 | nan | 1.0 |
| 0.0 | 9.04 | 9900 | nan | 1.0 |
| 0.0 | 9.32 | 10200 | nan | 1.0 |
| 0.0 | 9.59 | 10500 | nan | 1.0 |
| 0.0 | 9.86 | 10800 | nan | 1.0 |
| 0.0 | 10.14 | 11100 | nan | 1.0 |
| 0.0 | 10.41 | 11400 | nan | 1.0 |
| 0.0 | 10.68 | 11700 | nan | 1.0 |
| 0.0 | 10.96 | 12000 | nan | 1.0 |
| 0.0 | 11.23 | 12300 | nan | 1.0 |
| 0.0 | 11.51 | 12600 | nan | 1.0 |
| 0.0 | 11.78 | 12900 | nan | 1.0 |
| 0.0 | 12.05 | 13200 | nan | 1.0 |
| 0.0 | 12.33 | 13500 | nan | 1.0 |
| 0.0 | 12.6 | 13800 | nan | 1.0 |
| 0.0 | 12.88 | 14100 | nan | 1.0 |
| 0.0 | 13.15 | 14400 | nan | 1.0 |
| 0.0 | 13.42 | 14700 | nan | 1.0 |
| 0.0 | 13.7 | 15000 | nan | 1.0 |
| 0.0 | 13.97 | 15300 | nan | 1.0 |
| 0.0 | 14.25 | 15600 | nan | 1.0 |
| 0.0 | 14.52 | 15900 | nan | 1.0 |
| 0.0 | 14.79 | 16200 | nan | 1.0 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- Languages
- tr
- Created
- Jan 1, 2024
- Updated
- Jan 15, 2024