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--- |
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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: wav2vec2-base |
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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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# wav2vec2-base |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the galsenai/waxal_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7504 |
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- Accuracy: 0.8632 |
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- Precision: 0.9380 |
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- F1: 0.8954 |
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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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| 4.3647 | 2.53 | 500 | 4.8202 | 0.0117 | 0.0134 | 0.0032 | |
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| 2.6202 | 5.05 | 1000 | 4.2238 | 0.0625 | 0.0781 | 0.0355 | |
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| 1.38 | 7.58 | 1500 | 3.6392 | 0.2941 | 0.5211 | 0.3174 | |
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| 0.8601 | 10.1 | 2000 | 2.7953 | 0.4907 | 0.7446 | 0.5657 | |
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| 0.5645 | 12.63 | 2500 | 1.9829 | 0.6862 | 0.8363 | 0.7421 | |
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| 0.4009 | 15.15 | 3000 | 1.4535 | 0.7635 | 0.9000 | 0.8174 | |
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| 0.3054 | 17.68 | 3500 | 1.1426 | 0.7882 | 0.9058 | 0.8298 | |
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| 0.2448 | 20.2 | 4000 | 0.9860 | 0.8189 | 0.9206 | 0.8593 | |
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| 0.2116 | 22.73 | 4500 | 0.8820 | 0.8325 | 0.9261 | 0.8711 | |
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| 0.1863 | 25.25 | 5000 | 0.8191 | 0.8465 | 0.9366 | 0.8848 | |
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| 0.1701 | 27.78 | 5500 | 0.7504 | 0.8632 | 0.9380 | 0.8954 | |
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| 0.1558 | 30.3 | 6000 | 0.7665 | 0.8609 | 0.9398 | 0.8956 | |
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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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