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--- |
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language: |
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- sn |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- whisper-event and peft-lora |
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- generated_from_trainer |
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base_model: openai/whisper-tiny |
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datasets: |
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- Kittech/kittech_shona_dataset |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Sn - Bright Chirindo |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: Kingdom Truth International Ministries sermons |
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type: Kittech/kittech_shona_dataset |
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config: sn_zw |
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split: test |
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args: sn_zw |
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metrics: |
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- type: wer |
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value: 208.88577256501785 |
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name: Wer |
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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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# Whisper Small Sn - Bright Chirindo |
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This model is a fine-tuned version of [kittech/whisper-tiny-sn](https://huggingface.co/kittech/whisper-tiny-sn) on the Kingdom Truth International Ministries sermons dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9243 |
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- Wer: 208.8858 |
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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: 1e-05 |
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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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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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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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| 2.5155 | 357.1429 | 2500 | 2.9250 | 212.4044 | |
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| 2.1292 | 714.2857 | 5000 | 2.9243 | 208.8858 | |
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### Framework versions |
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- PEFT 0.10.1.dev0 |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.2.dev0 |
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- Tokenizers 0.19.1 |
