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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: r-f/wav2vec-english-speech-emotion-recognition |
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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: 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 [r-f/wav2vec-english-speech-emotion-recognition](https://huggingface.co/r-f/wav2vec-english-speech-emotion-recognition) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1011 |
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- Accuracy: 0.9724 |
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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: 0.001 |
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- train_batch_size: 10 |
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- eval_batch_size: 5 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 15 |
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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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| 1.4918 | 1.0 | 232 | 1.3591 | 0.3672 | |
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| 1.0899 | 2.0 | 464 | 0.9012 | 0.5672 | |
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| 0.9523 | 3.0 | 696 | 1.2430 | 0.4862 | |
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| 0.8062 | 4.0 | 928 | 0.6423 | 0.7759 | |
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| 0.5591 | 5.0 | 1160 | 0.5161 | 0.8276 | |
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| 0.4538 | 6.0 | 1392 | 0.6369 | 0.8069 | |
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| 0.3527 | 7.0 | 1624 | 0.2526 | 0.9207 | |
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| 0.3833 | 8.0 | 1856 | 0.2226 | 0.9328 | |
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| 0.2532 | 9.0 | 2088 | 0.1955 | 0.9466 | |
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| 0.1296 | 10.0 | 2320 | 0.1860 | 0.9483 | |
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| 0.144 | 11.0 | 2552 | 0.1885 | 0.9552 | |
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| 0.1976 | 12.0 | 2784 | 0.1243 | 0.9655 | |
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| 0.0147 | 13.0 | 3016 | 0.1375 | 0.9655 | |
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| 0.0149 | 14.0 | 3248 | 0.1061 | 0.9776 | |
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| 0.0199 | 15.0 | 3480 | 0.1011 | 0.9724 | |
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### Framework versions |
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- Transformers 4.53.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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