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  1. README.md +88 -0
  2. generation_config.json +254 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - mr
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+ license: apache-2.0
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+ base_model: Viraj008/whisper-small-mr_v3
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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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+ - fsicoli/common_voice_19_0
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+ - ylacombe/google-marathi
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+ - google/fleurs
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Small MR v4 - Viraj Patil
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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: mozilla-foundation/common_voice_17_0
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+ config: mr
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+ split: None
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+ args: 'config: mr, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 34.49746734204212
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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 Small MR v4 - Viraj Patil
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+
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+ This model is a fine-tuned version of [Viraj008/whisper-small-mr_v3](https://huggingface.co/Viraj008/whisper-small-mr_v3) 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: 0.2132
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+ - Wer: 34.4975
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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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+
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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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+ | 0.1241 | 0.5355 | 1000 | 0.2290 | 40.3892 |
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+ | 0.0681 | 1.0710 | 2000 | 0.2150 | 36.1037 |
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+ | 0.0576 | 1.6064 | 3000 | 0.2081 | 35.2573 |
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+ | 0.0399 | 2.1419 | 4000 | 0.2132 | 34.4975 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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