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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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datasets: |
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- superb |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-ks-linear_lrX1000 |
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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-ks-linear_lrX1000 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5661 |
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- Accuracy: 0.8325 |
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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: 0.03 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1024 |
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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: 10.0 |
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- mixed_precision_training: Native AMP |
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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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| 0.7558 | 1.0 | 50 | 1.0584 | 0.6462 | |
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| 0.5971 | 2.0 | 100 | 0.7816 | 0.7510 | |
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| 0.5382 | 3.0 | 150 | 0.7870 | 0.7520 | |
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| 0.5045 | 4.0 | 200 | 0.6647 | 0.7880 | |
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| 0.4717 | 5.0 | 250 | 1.1572 | 0.6053 | |
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| 0.4651 | 6.0 | 300 | 0.6387 | 0.7945 | |
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| 0.4205 | 7.0 | 350 | 0.5661 | 0.8325 | |
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| 0.4423 | 8.0 | 400 | 0.7100 | 0.7846 | |
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| 0.426 | 9.0 | 450 | 0.7054 | 0.7829 | |
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| 0.4067 | 10.0 | 500 | 0.6288 | 0.8114 | |
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### Framework versions |
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- Transformers 4.22.0.dev0 |
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- Pytorch 1.11.0+cu115 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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