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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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base_model: facebook/wav2vec2-large-xlsr-53 |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1638 |
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- Accuracy: 0.975 |
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## Model description |
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The model Urdu audio and classify in following categories |
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* Angry |
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* Happy |
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* Neutral |
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* Sad |
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## Training and evaluation data |
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The dataset is available at |
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https://www.kaggle.com/datasets/kingabzpro/urdu-emotion-dataset |
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## Training procedure |
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Training code is available at |
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https://www.kaggle.com/code/chtalhaanwar/urdu-emotions-hf |
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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: 32 |
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- eval_batch_size: 32 |
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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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- num_epochs: 50 |
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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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| 1.3838 | 1.0 | 10 | 1.3907 | 0.225 | |
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| 1.3732 | 2.0 | 20 | 1.3872 | 0.2125 | |
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| 1.3354 | 3.0 | 30 | 1.3116 | 0.6625 | |
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| 1.2689 | 4.0 | 40 | 1.1820 | 0.6375 | |
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| 1.1179 | 5.0 | 50 | 1.0075 | 0.7 | |
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| 0.9962 | 6.0 | 60 | 0.8707 | 0.7125 | |
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| 0.8842 | 7.0 | 70 | 0.7485 | 0.7625 | |
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| 0.786 | 8.0 | 80 | 0.6326 | 0.8 | |
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| 0.6757 | 9.0 | 90 | 0.5995 | 0.8 | |
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| 0.6104 | 10.0 | 100 | 0.4835 | 0.825 | |
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| 0.5821 | 11.0 | 110 | 0.3886 | 0.9 | |
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| 0.4721 | 12.0 | 120 | 0.3935 | 0.8625 | |
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| 0.3976 | 13.0 | 130 | 0.3020 | 0.925 | |
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| 0.4483 | 14.0 | 140 | 0.3171 | 0.9 | |
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| 0.2665 | 15.0 | 150 | 0.3016 | 0.9125 | |
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| 0.2119 | 16.0 | 160 | 0.2722 | 0.925 | |
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| 0.3376 | 17.0 | 170 | 0.3163 | 0.8875 | |
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| 0.1518 | 18.0 | 180 | 0.2681 | 0.9125 | |
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| 0.1559 | 19.0 | 190 | 0.3074 | 0.925 | |
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| 0.1031 | 20.0 | 200 | 0.3526 | 0.8875 | |
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| 0.1557 | 21.0 | 210 | 0.2254 | 0.9375 | |
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| 0.0846 | 22.0 | 220 | 0.2410 | 0.9375 | |
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| 0.0733 | 23.0 | 230 | 0.2369 | 0.925 | |
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| 0.0964 | 24.0 | 240 | 0.2273 | 0.9375 | |
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| 0.0574 | 25.0 | 250 | 0.2066 | 0.95 | |
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| 0.1113 | 26.0 | 260 | 0.2941 | 0.9125 | |
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| 0.1313 | 27.0 | 270 | 0.2715 | 0.925 | |
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| 0.0851 | 28.0 | 280 | 0.1725 | 0.9625 | |
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| 0.0402 | 29.0 | 290 | 0.2221 | 0.95 | |
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| 0.1075 | 30.0 | 300 | 0.2199 | 0.9625 | |
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| 0.0418 | 31.0 | 310 | 0.1699 | 0.95 | |
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| 0.1869 | 32.0 | 320 | 0.2287 | 0.9625 | |
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| 0.0637 | 33.0 | 330 | 0.3230 | 0.9125 | |
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| 0.0483 | 34.0 | 340 | 0.1602 | 0.975 | |
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| 0.0891 | 35.0 | 350 | 0.1615 | 0.975 | |
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| 0.0359 | 36.0 | 360 | 0.1571 | 0.975 | |
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| 0.1006 | 37.0 | 370 | 0.1809 | 0.9625 | |
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| 0.0417 | 38.0 | 380 | 0.1923 | 0.9625 | |
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| 0.0346 | 39.0 | 390 | 0.2035 | 0.9625 | |
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| 0.0417 | 40.0 | 400 | 0.1737 | 0.9625 | |
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| 0.0396 | 41.0 | 410 | 0.1833 | 0.9625 | |
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| 0.0202 | 42.0 | 420 | 0.1946 | 0.9625 | |
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| 0.0137 | 43.0 | 430 | 0.1785 | 0.9625 | |
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| 0.0214 | 44.0 | 440 | 0.1841 | 0.9625 | |
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| 0.0304 | 45.0 | 450 | 0.1690 | 0.9625 | |
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| 0.0199 | 46.0 | 460 | 0.1646 | 0.975 | |
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| 0.0122 | 47.0 | 470 | 0.1622 | 0.975 | |
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| 0.0324 | 48.0 | 480 | 0.1615 | 0.975 | |
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| 0.0269 | 49.0 | 490 | 0.1625 | 0.975 | |
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| 0.0245 | 50.0 | 500 | 0.1638 | 0.975 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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