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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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metrics: |
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- accuracy |
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model_index: |
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name: wav2vec2-lg-xlsr-en-speech-emotion-recognition |
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--- |
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# Speech Emotion Recognition By Fine-Tuning Wav2Vec 2.0 |
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The model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) for a Speech Emotion Recognition (SER) task. |
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The dataset used to fine-tune the original pre-trained model is the [RAVDESS dataset](https://zenodo.org/record/1188976#.YO6yI-gzaUk). This dataset provides 1440 samples of recordings from actors performing on 8 different emotions in English, which are: |
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```python |
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emotions = ['angry', 'calm', 'disgust', 'fearful', 'happy', 'neutral', 'sad', 'surprised'] |
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``` |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5023 |
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- Accuracy: 0.8223 |
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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: 0.0001 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- mixed_precision_training: Native AMP |
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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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| 2.0752 | 0.21 | 30 | 2.0505 | 0.1359 | |
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| 2.0119 | 0.42 | 60 | 1.9340 | 0.2474 | |
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| 1.8073 | 0.63 | 90 | 1.5169 | 0.3902 | |
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| 1.5418 | 0.84 | 120 | 1.2373 | 0.5610 | |
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| 1.1432 | 1.05 | 150 | 1.1579 | 0.5610 | |
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| 0.9645 | 1.26 | 180 | 0.9610 | 0.6167 | |
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| 0.8811 | 1.47 | 210 | 0.8063 | 0.7178 | |
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| 0.8756 | 1.68 | 240 | 0.7379 | 0.7352 | |
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| 0.8208 | 1.89 | 270 | 0.6839 | 0.7596 | |
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| 0.7118 | 2.1 | 300 | 0.6664 | 0.7735 | |
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| 0.4261 | 2.31 | 330 | 0.6058 | 0.8014 | |
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| 0.4394 | 2.52 | 360 | 0.5754 | 0.8223 | |
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| 0.4581 | 2.72 | 390 | 0.4719 | 0.8467 | |
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| 0.3967 | 2.93 | 420 | 0.5023 | 0.8223 | |
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## Citation |
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```bibtex |
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@misc {enrique_hernández_calabrés_2024, |
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author = { {Enrique Hernández Calabrés} }, |
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title = { wav2vec2-lg-xlsr-en-speech-emotion-recognition (Revision 17cf17c) }, |
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year = 2024, |
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url = { https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition }, |
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doi = { 10.57967/hf/2045 }, |
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publisher = { Hugging Face } |
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} |
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``` |
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## Contact |
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Any doubt, contact me on [Twitter](https://twitter.com/ehcalabres). |
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### Framework versions |
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- Transformers 4.8.2 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.9.0 |
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- Tokenizers 0.10.3 |
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