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wav2vec2-large-xlsr-indian-language-classification-featureExtractor
yashcode00/wav2vec2-large-xlsr-indian-language-classification-featureExtractor
wav2vec2-large-xlsr-indian-language-classification-featureExtractor is a machine learning model from yashcode00. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Sep 12, 2023
- Updated
- Dec 1, 2023
- SHA
- 6914615b
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-indian-language-classification-featureExtractor
This model is a fine-tuned version of yashcode00/wav2vec2-large-xlsr-indian-language-classification-featureExtractor on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1164
- Accuracy: 0.9677
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 300
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0194 | 203.39 | 1500 | 0.1154 | 0.9677 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Sep 12, 2023
- Updated
- Dec 1, 2023