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README.md
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---
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license: apache-2.0
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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-large-xlsr-53-AsanteTwi-05
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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: tw
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split: test
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args: tw
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metrics:
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- name: Wer
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type: wer
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value: 0.75
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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-large-xlsr-53-AsanteTwi-05
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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: 0.7657
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- Wer: 0.75
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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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- 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: 200
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- num_epochs: 150
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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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| 2.2241 | 16.67 | 100 | 2.1317 | 1.0 |
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| 1.5168 | 33.33 | 200 | 1.1019 | 0.8125 |
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| 0.7964 | 50.0 | 300 | 0.7658 | 0.75 |
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| 0.4985 | 66.67 | 400 | 0.6807 | 0.625 |
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| 0.3885 | 83.33 | 500 | 0.7197 | 0.5625 |
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| 0.3269 | 100.0 | 600 | 0.7616 | 0.5625 |
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| 0.2625 | 116.67 | 700 | 0.7000 | 0.6875 |
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| 0.2595 | 133.33 | 800 | 0.7425 | 0.6875 |
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| 0.2388 | 150.0 | 900 | 0.7657 | 0.75 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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