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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: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - minds14
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: GSoC_wavLM_DetectionOfIntonationalUnits
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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: minds14
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+ type: minds14
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+ config: en-US
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+ split: train
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+ args: en-US
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.04424778761061947
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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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+ # GSoC_wavLM_DetectionOfIntonationalUnits
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.6665
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+ - Accuracy: 0.0442
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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: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ | No log | 0.8 | 3 | 2.6398 | 0.0708 |
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+ | No log | 1.8667 | 7 | 2.6405 | 0.0973 |
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+ | 2.6341 | 2.9333 | 11 | 2.6580 | 0.0531 |
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+ | 2.6341 | 4.0 | 15 | 2.6572 | 0.0619 |
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+ | 2.6341 | 4.8 | 18 | 2.6609 | 0.0708 |
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+ | 2.6162 | 5.8667 | 22 | 2.6652 | 0.0708 |
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+ | 2.6162 | 6.9333 | 26 | 2.6658 | 0.0442 |
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+ | 2.6138 | 8.0 | 30 | 2.6665 | 0.0442 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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