End of training
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README.md
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- generated_from_trainer
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datasets:
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- common_voice_13_0
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model-index:
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- name: wav2vec2-large-xlsr-53-demo-colab
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results:
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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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# wav2vec2-large-xlsr-53-demo-colab
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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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## Model description
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type:
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- lr_scheduler_warmup_steps:
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- num_epochs: 20
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### Training results
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### Framework versions
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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-large-xlsr-53-demo-colab
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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: sah
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split: test
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args: sah
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metrics:
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- name: Wer
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type: wer
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value: 0.8174979851347721
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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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# wav2vec2-large-xlsr-53-demo-colab
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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: 0.9038
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- Wer: 0.8175
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## Model description
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 50
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- num_epochs: 20
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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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| 3.0574 | 3.33 | 50 | 2.9873 | 1.0 |
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| 2.8631 | 6.67 | 100 | 2.7208 | 1.0 |
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| 2.0621 | 10.0 | 150 | 1.3181 | 1.0321 |
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| 1.0109 | 13.33 | 200 | 0.9915 | 0.8863 |
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| 0.6483 | 16.67 | 250 | 0.9177 | 0.8362 |
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| 0.5217 | 20.0 | 300 | 0.9038 | 0.8175 |
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### Framework versions
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