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--- |
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base_model: microsoft/wavlm-base-plus |
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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: wavelm-study |
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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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# wavelm-study |
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This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6466 |
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- Accuracy: 0.8783 |
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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: 3e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 3 |
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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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| 0.9941 | 1.0 | 30 | 0.9388 | 0.6528 | |
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| 0.7785 | 2.0 | 60 | 0.7010 | 0.8655 | |
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| 0.7143 | 3.0 | 90 | 0.6466 | 0.8783 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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