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--- |
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license: apache-2.0 |
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base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english |
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tags: |
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- audio-classification |
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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: speech-emotion-recognition-wav2vec2 |
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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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# speech-emotion-recognition-wav2vec2 |
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2842 |
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- Accuracy: 0.9045 |
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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: 1.0 |
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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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| 2.1026 | 0.0236 | 10 | 2.0265 | 0.1592 | |
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| 1.9631 | 0.0472 | 20 | 2.0125 | 0.1993 | |
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| 1.9106 | 0.0708 | 30 | 1.8609 | 0.2417 | |
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| 1.715 | 0.0943 | 40 | 1.7659 | 0.3054 | |
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| 1.69 | 0.1179 | 50 | 1.5524 | 0.3785 | |
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| 1.4684 | 0.1415 | 60 | 1.4516 | 0.4057 | |
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| 1.3422 | 0.1651 | 70 | 1.2702 | 0.5354 | |
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| 1.2358 | 0.1887 | 80 | 0.9599 | 0.6899 | |
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| 0.9937 | 0.2123 | 90 | 0.8447 | 0.7394 | |
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| 0.7604 | 0.2358 | 100 | 0.8068 | 0.7453 | |
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| 0.7736 | 0.2594 | 110 | 0.6561 | 0.7913 | |
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| 0.6573 | 0.2830 | 120 | 0.6584 | 0.7830 | |
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| 0.5634 | 0.3066 | 130 | 0.5564 | 0.8066 | |
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| 0.5353 | 0.3302 | 140 | 0.5586 | 0.8184 | |
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| 0.3805 | 0.3538 | 150 | 0.6575 | 0.7818 | |
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| 0.6584 | 0.3774 | 160 | 0.4686 | 0.8538 | |
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| 0.4788 | 0.4009 | 170 | 0.4533 | 0.8514 | |
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| 0.4123 | 0.4245 | 180 | 0.5266 | 0.8432 | |
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| 0.4964 | 0.4481 | 190 | 0.5038 | 0.8325 | |
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| 0.4489 | 0.4717 | 200 | 0.5552 | 0.8208 | |
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| 0.4562 | 0.4953 | 210 | 0.4075 | 0.8526 | |
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| 0.5362 | 0.5189 | 220 | 0.4975 | 0.8184 | |
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| 0.3539 | 0.5425 | 230 | 0.4947 | 0.8267 | |
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| 0.4726 | 0.5660 | 240 | 0.4456 | 0.8514 | |
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| 0.3897 | 0.5896 | 250 | 0.3567 | 0.8715 | |
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| 0.2817 | 0.6132 | 260 | 0.3880 | 0.8644 | |
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| 0.3281 | 0.6368 | 270 | 0.3902 | 0.8679 | |
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| 0.311 | 0.6604 | 280 | 0.3243 | 0.9021 | |
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| 0.1768 | 0.6840 | 290 | 0.4162 | 0.8644 | |
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| 0.3748 | 0.7075 | 300 | 0.4482 | 0.8644 | |
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| 0.588 | 0.7311 | 310 | 0.3179 | 0.8950 | |
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| 0.402 | 0.7547 | 320 | 0.2955 | 0.9033 | |
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| 0.4068 | 0.7783 | 330 | 0.3212 | 0.8962 | |
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| 0.3622 | 0.8019 | 340 | 0.3931 | 0.8550 | |
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| 0.4407 | 0.8255 | 350 | 0.3467 | 0.8644 | |
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| 0.3474 | 0.8491 | 360 | 0.3149 | 0.8962 | |
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| 0.3449 | 0.8726 | 370 | 0.2829 | 0.9033 | |
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| 0.2673 | 0.8962 | 380 | 0.2566 | 0.9198 | |
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| 0.2998 | 0.9198 | 390 | 0.2614 | 0.9127 | |
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| 0.2721 | 0.9434 | 400 | 0.2786 | 0.9021 | |
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| 0.2717 | 0.9670 | 410 | 0.2891 | 0.9021 | |
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| 0.3277 | 0.9906 | 420 | 0.2842 | 0.9045 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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