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wav2vec2-base-finetuned-ks
FerhatDk/wav2vec2-base-finetuned-ks
wav2vec2-base-finetuned-ks is a audio classification model from FerhatDk. 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
- Sep 22, 2022
- Updated
- Jul 10, 2023
- SHA
- f4f820e8
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-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3550
- Accuracy: 0.8727
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 8 | 0.6840 | 0.6 |
| 0.6867 | 2.0 | 16 | 0.6780 | 0.6364 |
| 0.6742 | 3.0 | 24 | 0.6601 | 0.6182 |
| 0.6446 | 4.0 | 32 | 0.6294 | 0.6364 |
| 0.6299 | 5.0 | 40 | 0.6002 | 0.6727 |
| 0.6299 | 6.0 | 48 | 0.5755 | 0.7091 |
| 0.6021 | 7.0 | 56 | 0.5530 | 0.7273 |
| 0.5678 | 8.0 | 64 | 0.5036 | 0.8182 |
| 0.5512 | 9.0 | 72 | 0.4753 | 0.8545 |
| 0.4784 | 10.0 | 80 | 0.4184 | 0.9273 |
| 0.4784 | 11.0 | 88 | 0.4102 | 0.8909 |
| 0.4515 | 12.0 | 96 | 0.4444 | 0.8182 |
| 0.4878 | 13.0 | 104 | 0.3780 | 0.9091 |
| 0.4418 | 14.0 | 112 | 0.4570 | 0.8 |
| 0.4746 | 15.0 | 120 | 0.3870 | 0.8545 |
| 0.4746 | 16.0 | 128 | 0.3932 | 0.8364 |
| 0.4226 | 17.0 | 136 | 0.2779 | 0.9636 |
| 0.4301 | 18.0 | 144 | 0.3125 | 0.9455 |
| 0.3482 | 19.0 | 152 | 0.3212 | 0.9091 |
| 0.3611 | 20.0 | 160 | 0.3925 | 0.8364 |
| 0.3611 | 21.0 | 168 | 0.3389 | 0.8909 |
| 0.3507 | 22.0 | 176 | 0.3099 | 0.8727 |
| 0.3241 | 23.0 | 184 | 0.3120 | 0.8727 |
| 0.2533 | 24.0 | 192 | 0.2313 | 0.9455 |
| 0.2466 | 25.0 | 200 | 0.3550 | 0.8727 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Sep 22, 2022
- Updated
- Jul 10, 2023