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End of training
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- config.json +2 -3
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README.md
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name: common_voice_17_0
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type: common_voice_17_0
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config: ur
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split: test[:
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args: ur
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metrics:
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- name: Wer
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type: wer
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value:
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language:
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- ur
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pipeline_tag: automatic-speech-recognition
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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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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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model.generation_config.forced_decoder_ids = None
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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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ds = load_dataset("mozilla-foundation/common_voice_17_0", "ur", split="test")
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audio = ds[100]["audio"]
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result = pipe(audio)
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print("Original :", ds[100]['sentence'])
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print("Predicted :", result["text"])
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```
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```sh
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Original : اگر عمران خان ٹھیک کر رہے ہیں۔
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Predicted : اگر یمران خان ٹھیک کر رہے ہیں
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```
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It requires **1.8GiB** VRAM.
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## Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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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:
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- lr_scheduler_warmup_steps:
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- training_steps:
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer
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| 0.
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- Transformers 4.53.
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- Pytorch 2.8.0.dev20250319+cu128
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- Datasets 3.6.0
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- Tokenizers 0.21.2
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name: common_voice_17_0
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type: common_voice_17_0
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config: ur
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split: test[:600]
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args: ur
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metrics:
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- name: Wer
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type: wer
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value: 25.78416728902166
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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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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3534
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- Wer: 25.7842
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 4
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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: cosine
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- lr_scheduler_warmup_steps: 100
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- training_steps: 1500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.6764 | 0.2545 | 300 | 0.6244 | 44.9776 |
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| 0.5881 | 0.5089 | 600 | 0.5089 | 37.6214 |
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| 0.4662 | 0.7634 | 900 | 0.4349 | 32.1322 |
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| 0.3661 | 1.0178 | 1200 | 0.3634 | 26.5683 |
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| 0.2293 | 1.2723 | 1500 | 0.3534 | 25.7842 |
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### Framework versions
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- Transformers 4.53.1
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- Pytorch 2.8.0.dev20250319+cu128
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- Datasets 3.6.0
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- Tokenizers 0.21.2
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config.json
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"encoder_layerdrop": 0.0,
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"encoder_layers": 32,
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"eos_token_id": 50257,
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"forced_decoder_ids": null,
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"mask_feature_length": 10,
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"pad_token_id": 50257,
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.53.
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"use_cache":
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"vocab_size": 51866
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"pad_token_id": 50257,
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.53.1",
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"use_cache": false,
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"vocab_size": 51866
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}
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generation_config.json
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