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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: Valence-wav2vec2-base-EMOPIA |
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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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# Valence-wav2vec2-base-EMOPIA |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1044 |
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- Accuracy: 0.6761 |
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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: 1e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 3 |
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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_steps: 1000 |
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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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| 0.6979 | 1.0 | 269 | 0.6842 | 0.5915 | |
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| 0.69 | 2.0 | 538 | 0.6864 | 0.5775 | |
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| 0.6714 | 3.0 | 807 | 0.6900 | 0.5070 | |
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| 0.6357 | 4.0 | 1076 | 0.6514 | 0.5775 | |
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| 0.5678 | 5.0 | 1345 | 0.6612 | 0.6197 | |
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| 0.5152 | 6.0 | 1614 | 0.6496 | 0.6761 | |
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| 0.4826 | 7.0 | 1883 | 0.7743 | 0.6479 | |
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| 0.4707 | 8.0 | 2152 | 0.8348 | 0.6620 | |
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| 0.4742 | 9.0 | 2421 | 0.8808 | 0.6761 | |
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| 0.4857 | 10.0 | 2690 | 0.8734 | 0.7324 | |
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| 0.4779 | 11.0 | 2959 | 1.0206 | 0.6620 | |
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| 0.5063 | 12.0 | 3228 | 1.0737 | 0.6761 | |
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| 0.4776 | 13.0 | 3497 | 1.0966 | 0.6761 | |
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| 0.4716 | 14.0 | 3766 | 1.1046 | 0.6761 | |
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| 0.4672 | 15.0 | 4035 | 1.1044 | 0.6761 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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