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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v3-turbo
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_17_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-finetuned-fullsample-v1
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_17_0
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+ type: common_voice_17_0
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+ config: pt
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+ split: None
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+ args: pt
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 11.31198430186737
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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-finetuned-fullsample-v1
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+
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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: 0.3719
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+ - Wer: 11.3120
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 256
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+ - total_eval_batch_size: 32
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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: 600
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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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+ | 0.0094 | 8.1384 | 1000 | 0.2714 | 24.2485 |
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+ | 0.0008 | 16.2767 | 2000 | 0.3292 | 25.8955 |
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+ | 0.0011 | 24.4151 | 3000 | 0.3289 | 12.6679 |
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+ | 0.0003 | 32.5534 | 4000 | 0.3546 | 12.0631 |
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+ | 0.0015 | 40.6918 | 5000 | 0.3405 | 12.0647 |
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+ | 0.0002 | 48.8301 | 6000 | 0.3719 | 11.3120 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0.dev0
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+ - Pytorch 2.4.1+cu124
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+ - Datasets 3.0.2.dev0
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+ - Tokenizers 0.20.0
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