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End of training

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  1. README.md +84 -0
  2. generation_config.json +227 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-tiny
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - PolyAI/minds14
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-small-af-ZA
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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: PolyAI/minds14
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+ type: PolyAI/minds14
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+ config: af_za
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+ split: train+validation
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+ args: af_za
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.02925243770314193
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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-af-ZA
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0415
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+ - Wer Ortho: 0.0529
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+ - Wer: 0.0293
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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: 16
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+ - eval_batch_size: 16
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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: constant_with_warmup
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+ - lr_scheduler_warmup_steps: 5
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+ - training_steps: 700
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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 Ortho | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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+ | 0.0054 | 1.45 | 100 | 0.0312 | 0.0449 | 0.0228 |
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+ | 0.0025 | 2.9 | 200 | 0.0345 | 0.0456 | 0.0231 |
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+ | 0.0021 | 4.35 | 300 | 0.0325 | 0.0445 | 0.0206 |
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+ | 0.0018 | 5.8 | 400 | 0.0325 | 0.0449 | 0.0202 |
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+ | 0.0033 | 7.25 | 500 | 0.0390 | 0.0905 | 0.0654 |
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+ | 0.0043 | 8.7 | 600 | 0.0415 | 0.0577 | 0.0347 |
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+ | 0.0026 | 10.14 | 700 | 0.0415 | 0.0529 | 0.0293 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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