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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod12 |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_13_0 |
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type: common_voice_13_0 |
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config: id |
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split: test |
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args: id |
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metrics: |
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- type: wer |
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value: 0.29217367256637167 |
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name: Wer |
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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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod12 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3025 |
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- Wer: 0.2922 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: 10 |
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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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| 2.9131 | 1.0 | 464 | 2.9568 | 1.0 | |
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| 1.0005 | 2.0 | 928 | 0.6123 | 0.5699 | |
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| 0.5939 | 3.0 | 1392 | 0.4082 | 0.4204 | |
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| 0.4569 | 4.0 | 1856 | 0.3475 | 0.3725 | |
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| 0.4151 | 5.0 | 2320 | 0.3333 | 0.3413 | |
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| 0.3655 | 6.0 | 2784 | 0.3223 | 0.3234 | |
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| 0.3351 | 7.0 | 3248 | 0.3163 | 0.3078 | |
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| 0.3103 | 8.0 | 3712 | 0.3045 | 0.2956 | |
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| 0.3063 | 9.0 | 4176 | 0.3001 | 0.2900 | |
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| 0.3072 | 10.0 | 4640 | 0.3025 | 0.2922 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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