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- library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # Model Card for Model ID
 
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- ## Training Details
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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_Prod17
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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: 0.33453171091445427
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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_Prod17
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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: 0.3245
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+ - Wer: 0.3345
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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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+ | 2.9058 | 1.0 | 278 | 2.8200 | 1.0 |
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+ | 1.4695 | 2.0 | 556 | 0.7046 | 0.6722 |
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+ | 0.5298 | 3.0 | 834 | 0.4448 | 0.5104 |
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+ | 0.3601 | 4.0 | 1112 | 0.3744 | 0.4301 |
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+ | 0.2761 | 5.0 | 1390 | 0.3398 | 0.4128 |
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+ | 0.2092 | 6.0 | 1668 | 0.3356 | 0.3740 |
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+ | 0.1726 | 7.0 | 1946 | 0.3276 | 0.3538 |
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+ | 0.1461 | 8.0 | 2224 | 0.3210 | 0.3638 |
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+ | 0.1344 | 9.0 | 2502 | 0.3173 | 0.3441 |
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+ | 0.1173 | 10.0 | 2780 | 0.3215 | 0.3466 |
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+ | 0.1082 | 11.0 | 3058 | 0.3272 | 0.3402 |
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+ | 0.0981 | 12.0 | 3336 | 0.3245 | 0.3345 |
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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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