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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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_Prod2 |
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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: 1.0 |
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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_Prod2 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the xtreme_s dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8837 |
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- Wer: 1.0 |
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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: 0.005 |
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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: 200 |
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- num_epochs: 60 |
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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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| 3.962 | 3.08 | 100 | 2.8983 | 1.0 | |
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| 2.9085 | 6.15 | 200 | 2.8864 | 1.0 | |
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| 2.9094 | 9.23 | 300 | 2.9040 | 1.0 | |
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| 2.8976 | 12.31 | 400 | 2.9628 | 1.0 | |
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| 2.901 | 15.38 | 500 | 2.8694 | 1.0 | |
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| 2.8913 | 18.46 | 600 | 2.8954 | 1.0 | |
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| 2.8918 | 21.54 | 700 | 2.8726 | 1.0 | |
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| 2.892 | 24.62 | 800 | 2.8865 | 1.0 | |
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| 2.8856 | 27.69 | 900 | 2.9127 | 1.0 | |
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| 2.8893 | 30.77 | 1000 | 2.8989 | 1.0 | |
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| 2.8862 | 33.85 | 1100 | 2.8831 | 1.0 | |
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| 2.8853 | 36.92 | 1200 | 2.8960 | 1.0 | |
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| 2.8856 | 40.0 | 1300 | 2.8911 | 1.0 | |
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| 2.8849 | 43.08 | 1400 | 2.8926 | 1.0 | |
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| 2.8829 | 46.15 | 1500 | 2.8837 | 1.0 | |
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| 2.8812 | 49.23 | 1600 | 2.8859 | 1.0 | |
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| 2.8825 | 52.31 | 1700 | 2.8858 | 1.0 | |
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| 2.8833 | 55.38 | 1800 | 2.8856 | 1.0 | |
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| 2.88 | 58.46 | 1900 | 2.8837 | 1.0 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 1.18.3 |
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- Tokenizers 0.15.1 |
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