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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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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_Prod16 |
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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: 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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- name: Wer |
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type: wer |
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value: 0.3030973451327434 |
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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_Prod16 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) 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: 0.3355 |
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- Wer: 0.3031 |
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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: 12 |
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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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| 2.9606 | 1.0 | 278 | 2.9210 | 1.0 | |
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| 2.8429 | 2.0 | 556 | 2.1290 | 1.0 | |
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| 0.9644 | 3.0 | 834 | 0.5957 | 0.5614 | |
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| 0.6414 | 4.0 | 1112 | 0.4595 | 0.4643 | |
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| 0.5396 | 5.0 | 1390 | 0.4189 | 0.4090 | |
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| 0.4334 | 6.0 | 1668 | 0.3778 | 0.3670 | |
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| 0.3939 | 7.0 | 1946 | 0.3777 | 0.3544 | |
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| 0.3738 | 8.0 | 2224 | 0.3511 | 0.3355 | |
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| 0.3387 | 9.0 | 2502 | 0.3569 | 0.3240 | |
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| 0.3071 | 10.0 | 2780 | 0.3405 | 0.3165 | |
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| 0.3129 | 11.0 | 3058 | 0.3313 | 0.3065 | |
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| 0.2971 | 12.0 | 3336 | 0.3355 | 0.3031 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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