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IDAT_aug_concat_242_Wav2Vec
alirzb/IDAT_aug_concat_242_Wav2Vec
IDAT_aug_concat_242_Wav2Vec is a audio classification model from alirzb. Use it for the audio classification 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
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024
- SHA
- 2b55d70c
Base models
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. -->
IDAT_aug_concat_242_Wav2Vec
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6958
- Accuracy: 0.5
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7091 | 0.9714 | 17 | 0.6958 | 0.5 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 30, 2024
- Updated
- Aug 30, 2024