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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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+ - marsyas/gtzan
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: wav2vec2-base-finetuned-gtzan
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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: GTZAN
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+ type: marsyas/gtzan
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+ config: all
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+ split: train
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+ args: all
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.84
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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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+ # wav2vec2-base-finetuned-gtzan
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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 GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6933
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+ - Accuracy: 0.84
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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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: 12
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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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+ | 2.1735 | 0.99 | 56 | 2.1378 | 0.24 |
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+ | 1.7104 | 2.0 | 113 | 1.7187 | 0.52 |
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+ | 1.3864 | 2.99 | 169 | 1.5629 | 0.53 |
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+ | 1.1797 | 4.0 | 226 | 1.4349 | 0.62 |
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+ | 1.0675 | 4.99 | 282 | 1.0705 | 0.74 |
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+ | 0.9568 | 6.0 | 339 | 1.0412 | 0.74 |
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+ | 0.7465 | 6.99 | 395 | 0.8219 | 0.84 |
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+ | 0.6917 | 8.0 | 452 | 0.8743 | 0.78 |
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+ | 0.4634 | 8.99 | 508 | 0.8266 | 0.81 |
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+ | 0.4757 | 10.0 | 565 | 0.7233 | 0.86 |
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+ | 0.4341 | 10.99 | 621 | 0.8024 | 0.81 |
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+ | 0.3802 | 11.89 | 672 | 0.6933 | 0.84 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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