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End of training

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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: ntu-spml/distilhubert
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - arisha/stuttering
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilhubert-finetuned-stutteringdetection
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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: stuttering
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+ type: arisha/stuttering
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7692307692307693
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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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+ # distilhubert-finetuned-stutteringdetection
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+
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+ This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the stuttering dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8952
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+ - Accuracy: 0.7692
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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: 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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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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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+ | 1.1755 | 1.0 | 102 | 1.1561 | 0.5275 |
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+ | 0.9759 | 2.0 | 204 | 0.9051 | 0.6703 |
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+ | 0.5208 | 3.0 | 306 | 0.7956 | 0.7143 |
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+ | 0.3765 | 4.0 | 408 | 0.7282 | 0.8022 |
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+ | 0.2368 | 5.0 | 510 | 0.6921 | 0.8022 |
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+ | 0.1761 | 6.0 | 612 | 0.8270 | 0.7582 |
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+ | 0.3561 | 7.0 | 714 | 0.8967 | 0.7253 |
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+ | 0.2222 | 8.0 | 816 | 0.8201 | 0.8022 |
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+ | 0.0303 | 9.0 | 918 | 0.9433 | 0.7473 |
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+ | 0.019 | 10.0 | 1020 | 0.8952 | 0.7692 |
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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 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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