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End of training

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  1. README.md +83 -0
  2. generation_config.json +256 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ language:
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+ - vi
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+ base_model: openai/whisper-small-vi-v2
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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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 Vi - Anh Phuong
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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: Google fleurs
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+ type: google/fleurs
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+ config: vi_vn
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+ split: None
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+ args: 'config: hi, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 14.430800123571208
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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 Vi - Anh Phuong
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+
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+ This model is a fine-tuned version of [openai/whisper-small-vi-v2](https://huggingface.co/openai/whisper-small-vi-v2) on the Google fleurs dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4633
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+ - Wer: 14.4308
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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: 16
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+ - eval_batch_size: 4
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+ - seed: 42
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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: 6000
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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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+ | 0.0133 | 4.7619 | 1000 | 0.3913 | 15.3383 |
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+ | 0.0009 | 9.5238 | 2000 | 0.4180 | 14.3227 |
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+ | 0.0006 | 14.2857 | 3000 | 0.4382 | 14.6162 |
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+ | 0.0003 | 19.0476 | 4000 | 0.4496 | 14.4269 |
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+ | 0.0002 | 23.8095 | 5000 | 0.4594 | 14.4578 |
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+ | 0.0002 | 28.5714 | 6000 | 0.4633 | 14.4308 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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