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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- xtreme_s |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7 |
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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: xtreme_s |
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type: xtreme_s |
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config: fleurs.id_id |
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split: test |
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args: fleurs.id_id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5032929202215237 |
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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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7 |
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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 xtreme_s dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0673 |
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- Wer: 0.5033 |
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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: 0.001 |
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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: 600 |
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- num_epochs: 90 |
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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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| 5.2829 | 7.79 | 300 | 2.8538 | 1.0 | |
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| 1.9733 | 15.58 | 600 | 0.8923 | 0.7851 | |
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| 0.4186 | 23.38 | 900 | 0.8297 | 0.6443 | |
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| 0.2077 | 31.17 | 1200 | 0.8573 | 0.6011 | |
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| 0.1535 | 38.96 | 1500 | 0.9490 | 0.5800 | |
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| 0.1163 | 46.75 | 1800 | 1.0380 | 0.5652 | |
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| 0.1001 | 54.55 | 2100 | 0.9354 | 0.5417 | |
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| 0.0845 | 62.34 | 2400 | 1.0226 | 0.5364 | |
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| 0.0711 | 70.13 | 2700 | 1.0799 | 0.5220 | |
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| 0.0588 | 77.92 | 3000 | 1.0550 | 0.5050 | |
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| 0.0492 | 85.71 | 3300 | 1.0673 | 0.5033 | |
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### Framework versions |
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- Transformers 4.39.0 |
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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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