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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/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: audio_classification_example
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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: 0.07079646017699115
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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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# audio_classification_example
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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: 2.6501
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- Accuracy: 0.0708
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.6446 | 0.99 | 28 | 2.6533 | 0.0708 |
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| 2.6501 | 1.98 | 56 | 2.6360 | 0.0442 |
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| 2.6415 | 2.97 | 84 | 2.6452 | 0.0708 |
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| 2.6469 | 4.0 | 113 | 2.6508 | 0.0708 |
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| 2.6372 | 4.99 | 141 | 2.6463 | 0.0708 |
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| 2.6364 | 5.98 | 169 | 2.6467 | 0.0708 |
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| 2.6279 | 6.97 | 197 | 2.6497 | 0.0708 |
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| 2.6331 | 8.0 | 226 | 2.6510 | 0.0708 |
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| 2.6312 | 8.99 | 254 | 2.6504 | 0.0708 |
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| 2.6214 | 9.91 | 280 | 2.6501 | 0.0708 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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