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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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- 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-mvc-swahili |
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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: sw |
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split: test |
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args: sw |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.32237526397075045 |
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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-mvc-swahili |
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This model is a fine-tuned version of [alamsher/wav2vec2-large-xlsr-53-common-voice-sw](https://huggingface.co/alamsher/wav2vec2-large-xlsr-53-common-voice-sw) 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: inf |
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- Wer: 0.3224 |
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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: 0.0003 |
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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: 500 |
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- num_epochs: 2 |
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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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| No log | 0.17 | 100 | inf | 1.0 | |
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| No log | 0.34 | 200 | inf | 1.0 | |
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| No log | 0.5 | 300 | inf | 0.3420 | |
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| 3.3446 | 0.67 | 400 | inf | 0.3431 | |
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| 3.3446 | 0.84 | 500 | inf | 0.3500 | |
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| 3.3446 | 1.01 | 600 | inf | 0.3433 | |
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| 3.3446 | 1.17 | 700 | inf | 0.3347 | |
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| 0.1975 | 1.34 | 800 | inf | 0.3340 | |
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| 0.1975 | 1.51 | 900 | inf | 0.3307 | |
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| 0.1975 | 1.68 | 1000 | inf | 0.3233 | |
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| 0.1975 | 1.84 | 1100 | inf | 0.3224 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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