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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: 1.8681
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- Accuracy: 0.5175
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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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| 3.5459 | 1.0 | 200 | 3.5354 | 0.09 |
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| 3.1002 | 2.0 | 400 | 3.2000 | 0.1375 |
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| 2.8786 | 3.0 | 600 | 2.8955 | 0.175 |
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| 2.5762 | 4.0 | 800 | 2.6800 | 0.2325 |
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| 2.3834 | 5.0 | 1000 | 2.5289 | 0.2725 |
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| 2.3231 | 6.0 | 1200 | 2.2412 | 0.375 |
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| 1.9827 | 7.0 | 1400 | 2.0902 | 0.435 |
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| 1.9386 | 8.0 | 1600 | 1.9596 | 0.4725 |
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| 1.7323 | 9.0 | 1800 | 1.9183 | 0.4675 |
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| 1.7958 | 10.0 | 2000 | 1.8681 | 0.5175 |
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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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