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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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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-base-self-331-colab |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.15007215007215008 |
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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-self-331-colab |
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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 audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3282 |
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- Wer: 0.1501 |
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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: 1e-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: 300 |
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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 | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 2.3444 | 30.77 | 200 | 2.1940 | 0.9841 | |
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| 1.972 | 61.54 | 400 | 1.4582 | 0.8167 | |
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| 1.3875 | 92.31 | 600 | 0.8476 | 0.5902 | |
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| 0.9092 | 123.08 | 800 | 0.5445 | 0.3636 | |
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| 0.6382 | 153.85 | 1000 | 0.4129 | 0.2641 | |
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| 0.5789 | 184.62 | 1200 | 0.3497 | 0.1876 | |
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| 0.4632 | 215.38 | 1400 | 0.3478 | 0.1616 | |
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| 0.4474 | 246.15 | 1600 | 0.3394 | 0.1486 | |
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| 0.429 | 276.92 | 1800 | 0.3282 | 0.1501 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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