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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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metrics: |
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- accuracy |
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model-index: |
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- name: emotions_6_classes_small |
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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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# emotions_6_classes_small |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the 'Audio emotions' public dataset, available form https://www.kaggle.com/datasets/uldisvalainis/audio-emotions. |
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'Surprised' class was discarded due to lack of samples. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9106 |
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- Accuracy: 0.7920 |
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## Model description |
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Classifies audios into 6 emotions: |
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- Angry |
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- Happy |
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- Sad |
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- Neutral |
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- Fearful |
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- Disgusted |
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## Intended uses & limitations |
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This model was trained for educational purposes. |
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## Training and evaluation data |
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- Training: 80% |
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- Test: 20% |
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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: 3e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 30 |
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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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| 0.2009 | 0.99 | 19 | 0.6892 | 0.7891 | |
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| 0.2272 | 1.97 | 38 | 0.7235 | 0.7817 | |
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| 0.2196 | 2.96 | 57 | 0.7027 | 0.7809 | |
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| 0.2402 | 4.0 | 77 | 0.7953 | 0.7592 | |
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| 0.2301 | 4.99 | 96 | 0.7979 | 0.7699 | |
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| 0.1896 | 5.97 | 115 | 0.7533 | 0.7838 | |
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| 0.188 | 6.96 | 134 | 0.7483 | 0.7817 | |
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| 0.1573 | 8.0 | 154 | 0.8200 | 0.7756 | |
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| 0.1576 | 8.99 | 173 | 0.7623 | 0.7944 | |
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| 0.1452 | 9.97 | 192 | 0.7460 | 0.7944 | |
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| 0.1322 | 10.96 | 211 | 0.8031 | 0.7875 | |
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| 0.1353 | 12.0 | 231 | 0.7864 | 0.7883 | |
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| 0.1211 | 12.99 | 250 | 0.7934 | 0.7903 | |
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| 0.1165 | 13.97 | 269 | 0.7734 | 0.7936 | |
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| 0.0928 | 14.96 | 288 | 0.8743 | 0.7842 | |
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| 0.095 | 16.0 | 308 | 0.8483 | 0.7867 | |
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| 0.0824 | 16.99 | 327 | 0.8860 | 0.7850 | |
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| 0.0896 | 17.97 | 346 | 0.8314 | 0.7957 | |
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| 0.0874 | 18.96 | 365 | 0.8164 | 0.7936 | |
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| 0.081 | 20.0 | 385 | 0.8250 | 0.7993 | |
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| 0.0673 | 20.99 | 404 | 0.9118 | 0.7879 | |
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| 0.0716 | 21.97 | 423 | 0.8605 | 0.7912 | |
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| 0.0588 | 22.96 | 442 | 0.8470 | 0.7985 | |
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| 0.0579 | 24.0 | 462 | 0.8906 | 0.7920 | |
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| 0.0511 | 24.99 | 481 | 0.8853 | 0.7969 | |
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| 0.0488 | 25.97 | 500 | 0.8901 | 0.7973 | |
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| 0.0468 | 26.96 | 519 | 0.9083 | 0.7895 | |
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| 0.0505 | 28.0 | 539 | 0.9010 | 0.7903 | |
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| 0.0542 | 28.99 | 558 | 0.8924 | 0.7944 | |
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| 0.0542 | 29.61 | 570 | 0.9106 | 0.7920 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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