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README.md
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---
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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: Hubert_emotion-finetuned-gtzan-efficient
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results: []
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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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# Hubert_emotion-finetuned-gtzan-efficient
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This model is a fine-tuned version of [Rajaram1996/Hubert_emotion](https://huggingface.co/Rajaram1996/Hubert_emotion) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2341
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- Accuracy: 0.65
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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: 5e-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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- 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: 100
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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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| 2.2127 | 1.0 | 113 | 2.2191 | 0.25 |
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| 1.9102 | 2.0 | 226 | 2.0018 | 0.37 |
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| 1.7139 | 3.0 | 339 | 1.7588 | 0.4 |
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| 1.5825 | 4.0 | 452 | 1.5608 | 0.41 |
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| 1.1426 | 5.0 | 565 | 1.4300 | 0.5 |
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| 1.8976 | 6.0 | 678 | 1.1726 | 0.56 |
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| 0.9303 | 7.0 | 791 | 1.1559 | 0.56 |
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| 0.8845 | 8.0 | 904 | 1.1501 | 0.65 |
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| 0.2069 | 9.0 | 1017 | 1.2055 | 0.58 |
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| 1.9863 | 10.0 | 1130 | 1.0804 | 0.62 |
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| 2.0317 | 11.0 | 1243 | 1.2341 | 0.65 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.1.0.dev20230627+cu121
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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