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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: result |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9690721649484536 |
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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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# result |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9485 |
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- Accuracy: 0.9691 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 35 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.9231 | 3 | 1.7283 | 0.9072 | |
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| No log | 1.8462 | 6 | 1.7069 | 0.9072 | |
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| No log | 2.7692 | 9 | 1.6799 | 0.9485 | |
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| 1.7783 | 4.0 | 13 | 1.6130 | 0.9278 | |
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| 1.7783 | 4.9231 | 16 | 1.5587 | 0.9485 | |
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| 1.7783 | 5.8462 | 19 | 1.5084 | 0.9691 | |
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| 1.6476 | 6.7692 | 22 | 1.4736 | 0.9485 | |
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| 1.6476 | 8.0 | 26 | 1.4109 | 0.9691 | |
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| 1.6476 | 8.9231 | 29 | 1.3672 | 0.9485 | |
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| 1.4942 | 9.8462 | 32 | 1.3308 | 0.9588 | |
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| 1.4942 | 10.7692 | 35 | 1.2972 | 0.9588 | |
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| 1.4942 | 12.0 | 39 | 1.2477 | 0.9588 | |
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| 1.3605 | 12.9231 | 42 | 1.2180 | 0.9588 | |
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| 1.3605 | 13.8462 | 45 | 1.1982 | 0.9485 | |
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| 1.3605 | 14.7692 | 48 | 1.1668 | 0.9691 | |
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| 1.2591 | 16.0 | 52 | 1.1356 | 0.9691 | |
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| 1.2591 | 16.9231 | 55 | 1.1097 | 0.9691 | |
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| 1.2591 | 17.8462 | 58 | 1.0918 | 0.9691 | |
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| 1.1784 | 18.7692 | 61 | 1.0711 | 0.9691 | |
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| 1.1784 | 20.0 | 65 | 1.0505 | 0.9691 | |
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| 1.1784 | 20.9231 | 68 | 1.0345 | 0.9691 | |
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| 1.1179 | 21.8462 | 71 | 1.0211 | 0.9691 | |
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| 1.1179 | 22.7692 | 74 | 1.0102 | 0.9691 | |
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| 1.1179 | 24.0 | 78 | 0.9949 | 0.9691 | |
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| 1.0669 | 24.9231 | 81 | 0.9835 | 0.9794 | |
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| 1.0669 | 25.8462 | 84 | 0.9774 | 0.9691 | |
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| 1.0669 | 26.7692 | 87 | 0.9736 | 0.9588 | |
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| 1.0398 | 28.0 | 91 | 0.9644 | 0.9691 | |
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| 1.0398 | 28.9231 | 94 | 0.9588 | 0.9794 | |
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| 1.0398 | 29.8462 | 97 | 0.9533 | 0.9691 | |
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| 1.0303 | 30.7692 | 100 | 0.9496 | 0.9691 | |
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| 1.0303 | 32.0 | 104 | 0.9485 | 0.9691 | |
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| 1.0303 | 32.3077 | 105 | 0.9485 | 0.9691 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.1.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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