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Browse files- README.md +55 -0
- convert_unicode.py +16 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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license: mit
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base_model: microsoft/Phi-4-multimodal-instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: Phi-4-multimodal-instruct-asr-tr
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results: []
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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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# Phi-4-multimodal-instruct-asr-tr
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This model is a fine-tuned version of [microsoft/Phi-4-multimodal-instruct](https://huggingface.co/microsoft/Phi-4-multimodal-instruct) on an unknown dataset.
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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: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 5000
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.46.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.3.2
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- Tokenizers 0.20.3
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convert_unicode.py
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import json
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def convert_unicode_escapes(input_file, output_file):
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# Read the JSON data from the input file
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with open(input_file, 'r', encoding='utf-8') as f:
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data = json.load(f)
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# Write the JSON data to the output file with Unicode escapes decoded
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with open(output_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=4)
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if __name__ == "__main__":
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input_file = 'eval_before.json'
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output_file = 'eval_before_readable.json'
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convert_unicode_escapes(input_file, output_file)
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print(f"Converted JSON saved to {output_file}")
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e7482a2ff9e11e12e799e70115f5683304d33e5c0f49583ab10a24cefec5002
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size 5304
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