Downloads · 30 days
12
3% of all-time downloads
wav2vec2-commonvoice-tamil
nikhil6041/wav2vec2-commonvoice-tamil
wav2vec2-commonvoice-tamil is a automatic speech recognition model from nikhil6041. 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. --
All-time downloads
462
Public
Repo size
2.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin378 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 31, 2022
- Updated
- Mar 31, 2022
- SHA
- 6aa8b2d8
Datasets
Spaces
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-commonvoice-tamil
This model is a fine-tuned version of Harveenchadha/vakyansh-wav2vec2-tamil-tam-250 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 3.3415
- 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 400
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.384 | 1.69 | 200 | 3.3400 | 1.0 |
| 3.3085 | 3.39 | 400 | 3.3609 | 1.0 |
| 3.3008 | 5.08 | 600 | 3.3331 | 1.0 |
| 3.2852 | 6.78 | 800 | 3.3492 | 1.0 |
| 3.2908 | 8.47 | 1000 | 3.3318 | 1.0 |
| 3.2865 | 10.17 | 1200 | 3.3501 | 1.0 |
| 3.2826 | 11.86 | 1400 | 3.3403 | 1.0 |
| 3.2875 | 13.56 | 1600 | 3.3335 | 1.0 |
| 3.2899 | 15.25 | 1800 | 3.3311 | 1.0 |
| 3.2755 | 16.95 | 2000 | 3.3617 | 1.0 |
| 3.2877 | 18.64 | 2200 | 3.3317 | 1.0 |
| 3.2854 | 20.34 | 2400 | 3.3560 | 1.0 |
| 3.2878 | 22.03 | 2600 | 3.3332 | 1.0 |
| 3.2766 | 23.73 | 2800 | 3.3317 | 1.0 |
| 3.2943 | 25.42 | 3000 | 3.3737 | 1.0 |
| 3.2845 | 27.12 | 3200 | 3.3347 | 1.0 |
| 3.2765 | 28.81 | 3400 | 3.3415 | 1.0 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- mit
- Created
- Mar 31, 2022
- Updated
- Mar 31, 2022