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---
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license: apache-2.0
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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-lg-xlsr-en-speech-emotion-recognition-finetuned-gtzan
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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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# wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-gtzan
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This model is a fine-tuned version of [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7145
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- Accuracy: 0.88
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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: 4
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- eval_batch_size: 4
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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: 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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| 1.9771 | 1.0 | 225 | 1.7112 | 0.48 |
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| 1.0169 | 2.0 | 450 | 1.1513 | 0.62 |
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| 0.7104 | 3.0 | 675 | 0.8799 | 0.7 |
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| 1.5425 | 4.0 | 900 | 0.7419 | 0.8 |
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| 0.2908 | 5.0 | 1125 | 0.6713 | 0.8 |
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| 0.8275 | 6.0 | 1350 | 0.6961 | 0.84 |
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| 0.0298 | 7.0 | 1575 | 0.8689 | 0.82 |
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| 0.0163 | 8.0 | 1800 | 0.7662 | 0.86 |
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| 0.0162 | 9.0 | 2025 | 0.7143 | 0.88 |
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| 0.2649 | 10.0 | 2250 | 0.7145 | 0.88 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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