78 lines
2.0 KiB
Markdown
78 lines
2.0 KiB
Markdown
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---
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library_name: transformers
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language:
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- fa
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license: apache-2.0
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base_model: openai/whisper-large-v2
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_17_0
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model-index:
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- name: Whisper large-v2 Fa - Common Voice
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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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# Whisper large-v2 Fa - Common Voice
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 17.0 dataset.
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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: 16
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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=(0.9,0.999) 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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### Test results
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- Best test WER (Word Error Rate): 0.322
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- Best test CER (Character Error Rate): 0.106
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### Usage
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```python
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import torch
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from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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model_id = "aictsharif/whisper-large-v2-fa"
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model = AutoModelForSpeechSeq2Seq.from_pretrained(
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model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
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)
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model.to(device)
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processor = AutoProcessor.from_pretrained(model_id)
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pipe = pipeline(
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"automatic-speech-recognition",
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model=model,
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tokenizer=processor.tokenizer,
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feature_extractor=processor.feature_extractor,
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torch_dtype=torch_dtype,
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device=device,
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)
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result = pipe('sample.mp3')
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print(result["text"])
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```
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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