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wtimit-base-960h-normal30percent-all
kartikay101/wtimit-base-960h-normal30percent-all
wtimit-base-960h-normal30percent-all is a automatic speech recognition model from kartikay101. 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
- May 29, 2024
- Updated
- May 29, 2024
- SHA
- affe03ee
Base models
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. -->
wtimit-base-960h-normal30percent-all
This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8097
- Wer: 0.3692
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.32 | 1.3889 | 1000 | 0.3506 | 0.2804 |
| 0.2342 | 2.7778 | 2000 | 0.4413 | 0.2977 |
| 0.183 | 4.1667 | 3000 | 0.4847 | 0.3134 |
| 0.1389 | 5.5556 | 4000 | 0.5576 | 0.3291 |
| 0.1156 | 6.9444 | 5000 | 0.6021 | 0.3405 |
| 0.1003 | 8.3333 | 6000 | 0.6778 | 0.3632 |
| 0.0921 | 9.7222 | 7000 | 0.6309 | 0.3549 |
| 0.0771 | 11.1111 | 8000 | 0.7765 | 0.3823 |
| 0.0674 | 12.5 | 9000 | 0.7512 | 0.3722 |
| 0.0629 | 13.8889 | 10000 | 0.6964 | 0.3764 |
| 0.0575 | 15.2778 | 11000 | 0.8090 | 0.3812 |
| 0.0531 | 16.6667 | 12000 | 0.8377 | 0.3919 |
| 0.044 | 18.0556 | 13000 | 0.8246 | 0.3881 |
| 0.0427 | 19.4444 | 14000 | 0.8331 | 0.3826 |
| 0.0415 | 20.8333 | 15000 | 0.8166 | 0.3800 |
| 0.0356 | 22.2222 | 16000 | 0.8550 | 0.3916 |
| 0.0359 | 23.6111 | 17000 | 0.7968 | 0.3843 |
| 0.0311 | 25.0 | 18000 | 0.8020 | 0.3788 |
| 0.0251 | 26.3889 | 19000 | 0.8026 | 0.3684 |
| 0.0264 | 27.7778 | 20000 | 0.7937 | 0.3743 |
| 0.0248 | 29.1667 | 21000 | 0.8097 | 0.3692 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 29, 2024
- Updated
- May 29, 2024