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--- |
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license: apache-2.0 |
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base_model: AntonyG/fine-tune-wav2vec2-large-xls-r-1b-sw |
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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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model-index: |
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- name: finetuning-wav2vec-large-swahili-asr-model_v9 |
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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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should probably proofread and complete it, then remove this comment. --> |
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# finetuning-wav2vec-large-swahili-asr-model_v9 |
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This model is a fine-tuned version of [AntonyG/fine-tune-wav2vec2-large-xls-r-1b-sw](https://huggingface.co./AntonyG/fine-tune-wav2vec2-large-xls-r-1b-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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- eval_loss: 0.2818 |
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- eval_wer: 0.1945 |
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- eval_runtime: 657.4969 |
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- eval_samples_per_second: 17.142 |
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- eval_steps_per_second: 2.143 |
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- epoch: 9.69 |
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- step: 14000 |
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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: 15 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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