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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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- speech_commands |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: wav2vec |
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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: speech_commands |
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type: speech_commands |
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config: v0.01 |
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split: test |
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args: v0.01 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8938656280428432 |
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- name: F1 |
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type: f1 |
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value: 0.8871854520046679 |
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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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# wav2vec |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4992 |
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- Accuracy: 0.8939 |
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- F1: 0.8872 |
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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: 80 |
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- eval_batch_size: 80 |
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- seed: 42 |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.6895 | 1.0 | 639 | 0.7875 | 0.8773 | 0.7995 | |
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| 0.4171 | 2.0 | 1278 | 0.5445 | 0.8932 | 0.8675 | |
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| 0.2706 | 3.0 | 1917 | 0.4992 | 0.8939 | 0.8872 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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