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Runtime error
Runtime error
bag fix
Browse files- notebooks/CLI_Example.ipynb +0 -0
- pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/classifier.ckpt +1 -0
- pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/embedding_model.ckpt +1 -0
- pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/hyperparams.yaml +1 -0
- pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/label_encoder.ckpt +1 -0
- pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/mean_var_norm_emb.ckpt +1 -0
- scripts/output/audio.wav +0 -0
- scripts/train.py +3 -2
- scripts/training_config.json +2 -2
notebooks/CLI_Example.ipynb
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pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/classifier.ckpt
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C:/Users/konst/.cache/huggingface/hub/models--speechbrain--spkrec-xvect-voxceleb/snapshots/e2cc27f853f99bd5d539432f0cba3f124c059f71/classifier.ckpt
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pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/embedding_model.ckpt
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C:/Users/konst/.cache/huggingface/hub/models--speechbrain--spkrec-xvect-voxceleb/snapshots/e2cc27f853f99bd5d539432f0cba3f124c059f71/embedding_model.ckpt
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pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/hyperparams.yaml
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C:/Users/konst/.cache/huggingface/hub/models--speechbrain--spkrec-xvect-voxceleb/snapshots/e2cc27f853f99bd5d539432f0cba3f124c059f71/hyperparams.yaml
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pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/label_encoder.ckpt
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C:/Users/konst/.cache/huggingface/hub/models--speechbrain--spkrec-xvect-voxceleb/snapshots/e2cc27f853f99bd5d539432f0cba3f124c059f71/label_encoder.txt
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pretrained_models/EncoderClassifier-e3dcc8e5060144ec1668cd02c05772cd/mean_var_norm_emb.ckpt
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C:/Users/konst/.cache/huggingface/hub/models--speechbrain--spkrec-xvect-voxceleb/snapshots/e2cc27f853f99bd5d539432f0cba3f124c059f71/mean_var_norm_emb.ckpt
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scripts/output/audio.wav
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Binary file (34.9 kB). View file
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scripts/train.py
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@@ -66,5 +66,6 @@ if __name__ == "__main__":
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trainer.train()
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cloning_model.save_pretrained(Path(training_config["output_dir"]) /
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Path(cloning_model.config['model_path'].replace('/', '_')
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trainer.train()
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cloning_model.save_pretrained(Path(training_config["output_dir"]) /
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Path(cloning_model.config['model_path'].replace('/', '_')
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+ '_' + Path(training_config['audio_path']).stem)
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)
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scripts/training_config.json
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"lang": "en",
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"batch_size": 2,
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"learning_rate": 1e-4,
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"max_steps":
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"warmup_steps":
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}
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"lang": "en",
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"batch_size": 2,
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"learning_rate": 1e-4,
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"max_steps": 100,
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"warmup_steps": 20
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}
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