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--- |
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base_model: anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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datasets: |
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- superb |
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metrics: |
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- accuracy |
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model-index: |
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- name: testV4 |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: superb |
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type: superb |
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config: ks |
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split: validation |
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args: ks |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6209179170344219 |
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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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# testV4 |
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This model is a fine-tuned version of [anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test](https://huggingface.co/anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test) on the superb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9986 |
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- Accuracy: 0.6209 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 5.0 |
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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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| 2.3236 | 1.0 | 100 | 1.9986 | 0.6209 | |
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| 1.6222 | 2.0 | 200 | 1.5412 | 0.6209 | |
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| 1.4879 | 3.0 | 300 | 1.5255 | 0.6209 | |
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| 1.4797 | 4.0 | 400 | 1.5182 | 0.6209 | |
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| 1.4761 | 5.0 | 500 | 1.5151 | 0.6209 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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