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--- |
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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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model-index: |
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- name: wav2vec_final_output |
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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: v0.02 |
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split: test |
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args: v0.02 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.901840490797546 |
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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_final_output |
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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: 0.4410 |
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- Accuracy: 0.9018 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.4588 | 1.0 | 663 | 1.2309 | 0.8763 | |
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| 0.6109 | 2.0 | 1326 | 0.5745 | 0.8920 | |
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| 0.4153 | 3.0 | 1989 | 0.4884 | 0.8953 | |
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| 0.3227 | 4.0 | 2652 | 0.4574 | 0.8980 | |
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| 0.2806 | 5.0 | 3315 | 0.4412 | 0.8994 | |
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| 0.207 | 6.0 | 3978 | 0.4403 | 0.9014 | |
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| 0.2226 | 7.0 | 4641 | 0.4479 | 0.8998 | |
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| 0.2577 | 8.0 | 5304 | 0.4421 | 0.9014 | |
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| 0.2188 | 9.0 | 5967 | 0.4408 | 0.9016 | |
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| 0.2082 | 10.0 | 6630 | 0.4410 | 0.9018 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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