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wav2vec2-base-random-stop-classification-3
suyuanliu/wav2vec2-base-random-stop-classification-3
wav2vec2-base-random-stop-classification-3 is a audio classification model from suyuanliu. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- Model type
- wav2vec2
- Access
- Public
- Created
- Apr 16, 2023
- Updated
- Apr 16, 2023
- SHA
- 3eacf1ef
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-base-random-stop-classification-3
This model is a fine-tuned version of on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3662
- Accuracy: 0.8753
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6931 | 0.99 | 18 | 0.6542 | 0.6178 |
| 0.6854 | 1.97 | 36 | 0.6173 | 0.6696 |
| 0.6617 | 2.96 | 54 | 0.5338 | 0.7343 |
| 0.6747 | 4.0 | 73 | 0.6521 | 0.6757 |
| 0.5626 | 4.99 | 91 | 0.4320 | 0.8072 |
| 0.5127 | 5.97 | 109 | 0.4987 | 0.7834 |
| 0.486 | 6.96 | 127 | 0.3753 | 0.8467 |
| 0.4393 | 8.0 | 146 | 0.4076 | 0.8290 |
| 0.4191 | 8.99 | 164 | 0.3877 | 0.8454 |
| 0.4287 | 9.97 | 182 | 0.3613 | 0.8549 |
| 0.4161 | 10.96 | 200 | 0.3714 | 0.8556 |
| 0.3938 | 12.0 | 219 | 0.3561 | 0.8569 |
| 0.3736 | 12.99 | 237 | 0.3914 | 0.8583 |
| 0.3571 | 13.97 | 255 | 0.3917 | 0.8535 |
| 0.3711 | 14.96 | 273 | 0.4288 | 0.8222 |
| 0.3303 | 16.0 | 292 | 0.3680 | 0.8638 |
| 0.3355 | 16.99 | 310 | 0.3724 | 0.8631 |
| 0.3523 | 17.97 | 328 | 0.3741 | 0.8644 |
| 0.3384 | 18.96 | 346 | 0.3726 | 0.8597 |
| 0.3063 | 20.0 | 365 | 0.3705 | 0.8658 |
| 0.2984 | 20.99 | 383 | 0.3866 | 0.8604 |
| 0.2841 | 21.97 | 401 | 0.3897 | 0.8590 |
| 0.3057 | 22.96 | 419 | 0.3662 | 0.8699 |
| 0.2831 | 24.0 | 438 | 0.3627 | 0.8760 |
| 0.2863 | 24.66 | 450 | 0.3662 | 0.8753 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- Created
- Apr 16, 2023
- Updated
- Apr 16, 2023