Downloads · 30 days
6
2% of all-time downloads
wav2vec2-xls-r-300m-CV8-ro
ubamba98/wav2vec2-xls-r-300m-CV8-ro
wav2vec2-xls-r-300m-CV8-ro is a automatic speech recognition model from ubamba98. 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
356
Public
Repo size
17.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Mar 23, 2022
- SHA
- db8fade4
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-xls-r-300m-CV8-ro
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - RO dataset. It achieves the following results on the evaluation set:
- Loss: 0.1578
- Wer: 0.6040
- Cer: 0.0475
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.9736 | 3.62 | 500 | 2.9508 | 1.0 | 1.0 |
| 1.3293 | 7.25 | 1000 | 0.3330 | 0.8407 | 0.0862 |
| 0.956 | 10.87 | 1500 | 0.2042 | 0.6872 | 0.0602 |
| 0.9509 | 14.49 | 2000 | 0.2184 | 0.7088 | 0.0652 |
| 0.9272 | 18.12 | 2500 | 0.2312 | 0.7211 | 0.0703 |
| 0.8561 | 21.74 | 3000 | 0.2158 | 0.6838 | 0.0631 |
| 0.8258 | 25.36 | 3500 | 0.1970 | 0.6844 | 0.0601 |
| 0.7993 | 28.98 | 4000 | 0.1895 | 0.6698 | 0.0577 |
| 0.7525 | 32.61 | 4500 | 0.1845 | 0.6453 | 0.0550 |
| 0.7211 | 36.23 | 5000 | 0.1781 | 0.6274 | 0.0531 |
| 0.677 | 39.85 | 5500 | 0.1732 | 0.6188 | 0.0514 |
| 0.6517 | 43.48 | 6000 | 0.1691 | 0.6177 | 0.0503 |
| 0.6326 | 47.1 | 6500 | 0.1619 | 0.6045 | 0.0479 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Languages
- ro
- Created
- Mar 2, 2022
- Updated
- Mar 23, 2022