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README.md
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---
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license: apache-2.0
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base_model: facebook/hubert-base-ls960
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tags:
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- audio-classification
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- hubert
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- esc50
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: hubert-esc50-finetuned-v2
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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-esc50-finetuned-v2
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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 ESC-50 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8640
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- Accuracy: 0.5225
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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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- num_epochs: 10
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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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| 3.5023 | 1.0 | 200 | 3.4954 | 0.1025 |
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| 3.0745 | 2.0 | 400 | 3.1206 | 0.14 |
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| 2.7667 | 3.0 | 600 | 2.8674 | 0.18 |
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| 2.5477 | 4.0 | 800 | 2.6013 | 0.265 |
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| 2.3458 | 5.0 | 1000 | 2.5071 | 0.3125 |
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| 2.3287 | 6.0 | 1200 | 2.2673 | 0.395 |
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| 1.9078 | 7.0 | 1400 | 2.1068 | 0.4425 |
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| 1.8707 | 8.0 | 1600 | 2.0044 | 0.4775 |
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| 1.7355 | 9.0 | 1800 | 1.8945 | 0.52 |
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| 1.7396 | 10.0 | 2000 | 1.8640 | 0.5225 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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