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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - multilingual
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - multilingual
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper-Small-Multilingual-Uganda
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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: Bateesa/popolivoice, Bateesa/buaiir_voice_jap
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+ type: multilingual
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+ args: 'languages: japadhola, english; splits: train, test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 39.842067480258436
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+ ---
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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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+
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+ # Whisper-Small-Multilingual-Uganda
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Bateesa/popolivoice, Bateesa/buaiir_voice_jap dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7142
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+ - Wer: 39.8421
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 64
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 4000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-------:|:----:|:---------------:|:-------:|
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+ | 0.0373 | 11.4943 | 1000 | 0.6213 | 29.6482 |
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+ | 0.0125 | 22.9885 | 2000 | 0.6981 | 37.2577 |
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+ | 0.0008 | 34.4828 | 3000 | 0.6874 | 39.6267 |
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+ | 0.0007 | 45.9770 | 4000 | 0.7142 | 39.8421 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.8.0
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+ - Pytorch 2.11.0+cu130
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+ - Datasets 2.21.0
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+ - Tokenizers 0.22.2
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