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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: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: my_awesome_mind_model |
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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: audiofolder |
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type: audiofolder |
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config: initial_audio |
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split: test |
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args: initial_audio |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.2564102564102564 |
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- name: Precision |
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type: precision |
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value: 0.7142857142857143 |
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- name: Recall |
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type: recall |
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value: 0.15625 |
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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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# my_awesome_mind_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6889 |
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- F1: 0.2564 |
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- Precision: 0.7143 |
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- Recall: 0.1562 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 2 | 0.6914 | 0.2162 | 0.8 | 0.125 | |
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| No log | 2.0 | 4 | 0.6894 | 0.4815 | 0.5909 | 0.4062 | |
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| No log | 3.0 | 6 | 0.6887 | 0.3256 | 0.6364 | 0.2188 | |
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| No log | 4.0 | 8 | 0.6881 | 0.3415 | 0.7778 | 0.2188 | |
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| 0.6907 | 5.0 | 10 | 0.6883 | 0.3415 | 0.7778 | 0.2188 | |
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| 0.6907 | 6.0 | 12 | 0.6890 | 0.2564 | 0.7143 | 0.1562 | |
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| 0.6907 | 7.0 | 14 | 0.6894 | 0.2564 | 0.7143 | 0.1562 | |
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| 0.6907 | 8.0 | 16 | 0.6894 | 0.2105 | 0.6667 | 0.125 | |
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| 0.6907 | 9.0 | 18 | 0.6890 | 0.2564 | 0.7143 | 0.1562 | |
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| 0.6851 | 10.0 | 20 | 0.6889 | 0.2564 | 0.7143 | 0.1562 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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