Downloads · 30 days
11
3% of all-time downloads
xls-r-300m-hi
gagan3012/xls-r-300m-hi
xls-r-300m-hi is a automatic speech recognition model from gagan3012. 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
435
Public
Repo size
27.8 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
- Jan 30, 2022
- SHA
- f689a18e
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. -->
xls-r-300m-hi
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HI dataset. It achieves the following results on the evaluation set:
- Loss: 0.7522
- Wer: 1.0091
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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 5.0417 | 2.59 | 500 | 5.1484 | 1.0 |
| 3.3722 | 5.18 | 1000 | 3.3380 | 1.0001 |
| 1.9752 | 7.77 | 1500 | 1.3910 | 1.0074 |
| 1.5868 | 10.36 | 2000 | 1.0298 | 1.0084 |
| 1.4413 | 12.95 | 2500 | 0.9313 | 1.0175 |
| 1.3296 | 15.54 | 3000 | 0.8966 | 1.0194 |
| 1.2746 | 18.13 | 3500 | 0.8875 | 1.0097 |
| 1.2147 | 20.73 | 4000 | 0.8746 | 1.0089 |
| 1.1774 | 23.32 | 4500 | 0.8383 | 1.0198 |
| 1.129 | 25.91 | 5000 | 0.7848 | 1.0167 |
| 1.0995 | 28.5 | 5500 | 0.7992 | 1.0210 |
| 1.0665 | 31.09 | 6000 | 0.7878 | 1.0107 |
| 1.0321 | 33.68 | 6500 | 0.7653 | 1.0082 |
| 1.0068 | 36.27 | 7000 | 0.7635 | 1.0065 |
| 0.9916 | 38.86 | 7500 | 0.7728 | 1.0090 |
| 0.9735 | 41.45 | 8000 | 0.7688 | 1.0070 |
| 0.9745 | 44.04 | 8500 | 0.7455 | 1.0097 |
| 0.9677 | 46.63 | 9000 | 0.7605 | 1.0099 |
| 0.9313 | 49.22 | 9500 | 0.7527 | 1.0097 |
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
- hi
- Created
- Mar 2, 2022
- Updated
- Jan 30, 2022