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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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+ - 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: 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: 0.85
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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: 0.9600
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+ - Accuracy: 0.85
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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: 4
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+ - total_train_batch_size: 32
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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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+ | 2.2696 | 0.99 | 28 | 2.1350 | 0.45 |
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+ | 1.9724 | 1.98 | 56 | 1.7939 | 0.63 |
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+ | 1.7172 | 2.97 | 84 | 1.6356 | 0.58 |
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+ | 1.5428 | 4.0 | 113 | 1.4019 | 0.71 |
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+ | 1.3184 | 4.99 | 141 | 1.3236 | 0.73 |
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+ | 1.2897 | 5.98 | 169 | 1.1980 | 0.79 |
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+ | 1.1657 | 6.97 | 197 | 1.0928 | 0.84 |
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+ | 1.0407 | 8.0 | 226 | 1.0616 | 0.83 |
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+ | 0.9717 | 8.99 | 254 | 0.9931 | 0.87 |
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+ | 0.9158 | 9.91 | 280 | 0.9600 | 0.85 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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