Respair commited on
Commit
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Respair/Hibiki_ASR_Phonemizer

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v3
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper_JP
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+ results: []
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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_JP
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+
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+ This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2186
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+ - Wer: 21.6707
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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: 24
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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: 6000
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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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+ | 0.2101 | 0.8058 | 1000 | 0.2090 | 30.1840 |
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+ | 0.1369 | 1.6116 | 2000 | 0.1837 | 27.6756 |
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+ | 0.0838 | 2.4174 | 3000 | 0.1829 | 26.4036 |
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+ | 0.0454 | 3.2232 | 4000 | 0.1922 | 20.9549 |
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+ | 0.0434 | 4.0290 | 5000 | 0.2072 | 20.8898 |
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+ | 0.021 | 4.8348 | 6000 | 0.2186 | 21.6707 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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