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license: apache-2.0 |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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- wolof |
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metrics: |
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- accuracy |
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- precision |
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- f1 |
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model-index: |
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- name: hubert-base-ls960 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# hubert-base-ls960 |
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the galsenai/waxal_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1857 |
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- Accuracy: 0.6442 |
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- Precision: 0.8369 |
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- F1: 0.7121 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 30 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 120 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 32.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
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| 4.523 | 2.53 | 500 | 5.1547 | 0.0205 | 0.0047 | 0.0037 | |
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| 3.4187 | 5.05 | 1000 | 4.6287 | 0.0337 | 0.0256 | 0.0163 | |
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| 2.3533 | 7.58 | 1500 | 4.2550 | 0.0944 | 0.1033 | 0.0641 | |
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| 1.7145 | 10.1 | 2000 | 3.9540 | 0.1095 | 0.2091 | 0.0964 | |
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| 1.3245 | 12.63 | 2500 | 3.8557 | 0.1758 | 0.3609 | 0.1859 | |
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| 1.0729 | 15.15 | 3000 | 3.7411 | 0.2247 | 0.4918 | 0.2537 | |
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| 0.8955 | 17.68 | 3500 | 3.2683 | 0.3789 | 0.6162 | 0.4256 | |
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| 0.7697 | 20.2 | 4000 | 2.8749 | 0.4612 | 0.7106 | 0.5171 | |
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| 0.6864 | 22.73 | 4500 | 2.7251 | 0.5169 | 0.7437 | 0.5779 | |
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| 0.6061 | 25.25 | 5000 | 2.5061 | 0.5631 | 0.8043 | 0.6335 | |
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| 0.5777 | 27.78 | 5500 | 2.2830 | 0.6177 | 0.8183 | 0.6837 | |
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| 0.5304 | 30.3 | 6000 | 2.1857 | 0.6442 | 0.8369 | 0.7121 | |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.9.1.dev0 |
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- Tokenizers 0.13.2 |
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