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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- shemo |
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metrics: |
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- f1 |
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model-index: |
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- name: results |
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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: shemo |
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type: shemo |
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config: clean |
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split: None |
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args: clean |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8335174497965196 |
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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 [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the shemo dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6161 |
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- F1: 0.8335 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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- num_epochs: 25 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.1127 | 1.0 | 154 | 0.9244 | 0.3968 | |
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| 0.6982 | 2.0 | 308 | 0.5642 | 0.6435 | |
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| 0.6246 | 3.0 | 462 | 0.5049 | 0.6273 | |
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| 0.5097 | 4.0 | 616 | 0.4282 | 0.7246 | |
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| 0.4496 | 5.0 | 770 | 0.3280 | 0.8158 | |
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| 0.4476 | 6.0 | 924 | 0.4663 | 0.7978 | |
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| 0.2212 | 7.0 | 1078 | 0.3253 | 0.8641 | |
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| 0.1548 | 8.0 | 1232 | 0.9445 | 0.7420 | |
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| 0.3829 | 9.0 | 1386 | 0.7194 | 0.7880 | |
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| 0.0773 | 10.0 | 1540 | 0.5301 | 0.8657 | |
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| 0.2481 | 11.0 | 1694 | 0.5321 | 0.8812 | |
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| 0.0597 | 12.0 | 1848 | 0.6161 | 0.8335 | |
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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 2.19.2 |
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- Tokenizers 0.19.1 |
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