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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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: wav2vec2-base-960h-speech-commands |
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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: None |
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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: 0.8066546762589928 |
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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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# wav2vec2-base-960h-speech-commands |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1612 |
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- Accuracy: 0.8067 |
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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: 48 |
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- eval_batch_size: 48 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.745 | 1.0 | 824 | 1.9237 | 0.7648 | |
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| 0.5664 | 2.0 | 1648 | 1.1424 | 0.7878 | |
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| 0.4337 | 3.0 | 2472 | 1.1234 | 0.8013 | |
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| 0.3346 | 4.0 | 3296 | 1.1040 | 0.8035 | |
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| 0.2683 | 5.0 | 4120 | 1.3128 | 0.7905 | |
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| 0.3498 | 6.0 | 4944 | 1.2172 | 0.7972 | |
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| 0.2556 | 7.0 | 5768 | 1.1906 | 0.7986 | |
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| 0.226 | 8.0 | 6592 | 1.1081 | 0.8044 | |
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| 0.2317 | 9.0 | 7416 | 1.1068 | 0.8049 | |
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| 0.1144 | 10.0 | 8240 | 1.1612 | 0.8067 | |
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| 0.2143 | 11.0 | 9064 | 1.1577 | 0.8031 | |
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| 0.1668 | 12.0 | 9888 | 1.1343 | 0.8058 | |
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| 0.2504 | 13.0 | 10712 | 1.0583 | 0.8067 | |
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| 0.218 | 14.0 | 11536 | 1.0677 | 0.8026 | |
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| 0.1025 | 15.0 | 12360 | 1.0690 | 0.8053 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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