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zarakun/wav2vec

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README.md ADDED
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+ ---
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+ library_name: transformers
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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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+ - speech_commands
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: wav2vec
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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: speech_commands
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+ type: speech_commands
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+ config: v0.01
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+ split: test
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+ args: v0.01
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8909444985394352
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+ - name: F1
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+ type: f1
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+ value: 0.8408887171290298
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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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+ # wav2vec
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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 speech_commands dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8904
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+ - Accuracy: 0.8909
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+ - F1: 0.8409
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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: 240
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+ - eval_batch_size: 240
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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: 3
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.4272 | 1.0 | 213 | 1.3926 | 0.8845 | 0.8359 |
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+ | 0.9354 | 2.0 | 426 | 0.9938 | 0.8877 | 0.8598 |
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+ | 0.7761 | 3.0 | 639 | 0.8904 | 0.8909 | 0.8409 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/wav2vec2-base",
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+ "activation_dropout": 0.0,
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+ "apply_spec_augment": true,
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+ "architectures": [
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+ "Wav2Vec2ForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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