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wav2vec2-large-xlsr-tamil-commonvoice
nikhil6041/wav2vec2-large-xlsr-tamil-commonvoice
wav2vec2-large-xlsr-tamil-commonvoice 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 7, 2021
- SHA
- b692d6d6
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-large-xlsr-tamil-commonvoice
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.6145
- Wer: 0.8512
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: 200
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.0478 | 1.05 | 100 | 3.3867 | 1.0 |
| 3.2522 | 2.11 | 200 | 3.2770 | 1.0 |
| 3.1689 | 3.16 | 300 | 3.1135 | 1.0039 |
| 2.9278 | 4.21 | 400 | 2.0485 | 1.3109 |
| 1.3592 | 5.26 | 500 | 0.8044 | 1.0988 |
| 0.7472 | 6.32 | 600 | 0.6571 | 0.9474 |
| 0.5842 | 7.37 | 700 | 0.6079 | 0.9477 |
| 0.4831 | 8.42 | 800 | 0.6083 | 0.9491 |
| 0.4259 | 9.47 | 900 | 0.5916 | 0.8973 |
| 0.3817 | 10.53 | 1000 | 0.6070 | 0.9147 |
| 0.338 | 11.58 | 1100 | 0.5873 | 0.8617 |
| 0.3123 | 12.63 | 1200 | 0.5983 | 0.8844 |
| 0.287 | 13.68 | 1300 | 0.6146 | 0.8988 |
| 0.2706 | 14.74 | 1400 | 0.6068 | 0.8754 |
| 0.2505 | 15.79 | 1500 | 0.5996 | 0.8638 |
| 0.2412 | 16.84 | 1600 | 0.6106 | 0.8481 |
| 0.2176 | 17.89 | 1700 | 0.6152 | 0.8520 |
| 0.2255 | 18.95 | 1800 | 0.6150 | 0.8540 |
| 0.216 | 20.0 | 1900 | 0.6145 | 0.8512 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu102
- Datasets 1.13.3
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Nov 7, 2021