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README.md
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---
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tags:
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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: trillsson3-ft-keyword-spotting
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: superb
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type: superb
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config: ks
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split: train
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args: ks
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9024713150926743
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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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# trillsson3-ft-keyword-spotting
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This model is a fine-tuned version of [vumichien/nonsemantic-speech-trillsson3](https://huggingface.co/vumichien/nonsemantic-speech-trillsson3) on the superb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3322
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- Accuracy: 0.9025
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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: 0.0003
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- train_batch_size: 32
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- eval_batch_size: 64
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- seed: 0
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 64
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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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| 1.1824 | 1.0 | 798 | 0.6478 | 0.7489 |
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| 0.7448 | 2.0 | 1596 | 0.4274 | 0.8728 |
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| 0.7089 | 3.0 | 2394 | 0.3723 | 0.8950 |
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| 0.6781 | 4.0 | 3192 | 0.3563 | 0.9041 |
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| 0.6386 | 5.0 | 3990 | 0.3441 | 0.8986 |
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| 0.6342 | 6.0 | 4788 | 0.3380 | 0.8994 |
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| 0.6275 | 7.0 | 5586 | 0.3376 | 0.8982 |
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| 0.6349 | 8.0 | 6384 | 0.3333 | 0.9014 |
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| 0.6261 | 9.0 | 7182 | 0.3295 | 0.9025 |
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| 0.6188 | 10.0 | 7980 | 0.3322 | 0.9025 |
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### Framework versions
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- Transformers 4.23.0.dev0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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