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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-small-ft_custom
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: None
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 2.3166023166023164
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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-ft_custom
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0000
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+ - Wer: 2.3166
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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: 8
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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: 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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+ | 0.0001 | 500.0 | 500 | 0.0001 | 37.0656 |
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+ | 0.0001 | 1000.0 | 1000 | 0.0001 | 37.0656 |
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+ | 0.0001 | 1500.0 | 1500 | 0.0001 | 2.3166 |
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+ | 0.0 | 2000.0 | 2000 | 0.0000 | 2.3166 |
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+ | 0.0 | 2500.0 | 2500 | 0.0000 | 2.3166 |
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+ | 0.0 | 3000.0 | 3000 | 0.0000 | 2.3166 |
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+ | 0.0 | 3500.0 | 3500 | 0.0000 | 2.3166 |
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+ | 0.0 | 4000.0 | 4000 | 0.0000 | 2.3166 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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