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wav2vec2-fine-tuning-960h-demo-google-colab
St4n/wav2vec2-fine-tuning-960h-demo-google-colab
wav2vec2-fine-tuning-960h-demo-google-colab is a automatic speech recognition model from St4n. 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
- Oct 9, 2023
- Updated
- Oct 9, 2023
- SHA
- 0056b970
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. -->
wav2vec2-fine-tuning-960h-demo-google-colab
This model is a fine-tuned version of St4n/wav2vec2-base-960h-demo-google-colab on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6643
- Wer: 0.9985
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: 16
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8048 | 5.81 | 500 | 0.5176 | 1.0 |
| 0.353 | 11.63 | 1000 | 0.5259 | 1.0 |
| 0.2843 | 17.44 | 1500 | 0.5725 | 0.9985 |
| 0.3374 | 23.26 | 2000 | 0.6190 | 0.9985 |
| 0.1625 | 29.07 | 2500 | 0.6643 | 0.9985 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 9, 2023
- Updated
- Oct 9, 2023