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README.md ADDED
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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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+ - 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: superb_ks_42
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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: superb
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+ type: superb
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+ config: ks
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+ split: validation
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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: 0.9833774639599883
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+ ---
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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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+
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+ # superb_ks_42
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+
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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 superb dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0857
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+ - Accuracy: 0.9834
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 4
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 1.5858 | 1.0 | 1597 | 0.1746 | 0.9701 |
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+ | 0.2268 | 2.0 | 3194 | 0.1038 | 0.9773 |
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+ | 0.1937 | 3.0 | 4791 | 0.0887 | 0.9797 |
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+ | 0.163 | 4.0 | 6388 | 0.0786 | 0.9826 |
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+ | 0.1468 | 5.0 | 7985 | 0.0982 | 0.9815 |
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+ | 0.1327 | 6.0 | 9582 | 0.0888 | 0.9821 |
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+ | 0.1175 | 7.0 | 11179 | 0.0967 | 0.9812 |
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+ | 0.1164 | 8.0 | 12776 | 0.0922 | 0.9815 |
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+ | 0.1023 | 9.0 | 14373 | 0.0875 | 0.9828 |
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+ | 0.0983 | 10.0 | 15970 | 0.0857 | 0.9834 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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