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wavlm-base_3
cloudwalkerw/wavlm-base_3
wavlm-base_3 is a audio classification model from cloudwalkerw. 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
- wavlm
- Access
- Public
- Created
- Sep 18, 2023
- Updated
- Sep 21, 2023
- SHA
- 38ffa639
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. -->
wavlm-base_3
This model is a fine-tuned version of microsoft/wavlm-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6534
- Accuracy: 0.8974
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 2
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2236 | 1.24 | 100 | 12.8495 | 0.4467 |
| 0.0514 | 2.48 | 200 | 16.3078 | 0.2677 |
| 0.0 | 3.72 | 300 | 17.5651 | 0.2597 |
| 0.3252 | 4.95 | 400 | 15.0382 | 0.1912 |
| 1.0577 | 6.19 | 500 | 0.6534 | 0.8974 |
| 0.6973 | 7.43 | 600 | 0.7352 | 0.1026 |
| 0.6939 | 8.67 | 700 | 0.6210 | 0.8974 |
| 0.6944 | 9.91 | 800 | 0.7129 | 0.1026 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wavlm
- Created
- Sep 18, 2023
- Updated
- Sep 21, 2023