83 lines
2.6 KiB
Markdown
83 lines
2.6 KiB
Markdown
---
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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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## Contact
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Any doubt, contact me on [Twitter](https://twitter.com/ehcalabres) (GitHub repo soon).
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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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