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End of training

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README.md ADDED
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+ ---
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+ language:
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+ - es
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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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+ - facebook/multilingual_librispeech
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Medium es - Dash Guitar
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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: facebook/multilingual_librispeech
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+ type: facebook/multilingual_librispeech
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+ config: spanish
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+ split: test
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+ args: spanish
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 7.085875706214689
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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 Medium es - Dash Guitar
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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 facebook/multilingual_librispeech dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1535
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+ - Wer Ortho: 7.0848
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+ - Wer: 7.0859
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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: 16
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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: constant_with_warmup
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+ - lr_scheduler_warmup_steps: 50
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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 Ortho | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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+ | 0.3349 | 0.02 | 500 | 0.1782 | 8.1526 | 8.1571 |
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+ | 0.309 | 0.04 | 1000 | 0.1702 | 7.5899 | 7.5921 |
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+ | 0.2814 | 0.05 | 1500 | 0.1680 | 8.0103 | 8.0124 |
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+ | 0.3067 | 0.07 | 2000 | 0.1665 | 8.1007 | 8.1028 |
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+ | 0.3223 | 0.09 | 2500 | 0.1751 | 9.2272 | 9.2294 |
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+ | 0.2696 | 0.11 | 3000 | 0.1583 | 7.2374 | 7.2395 |
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+ | 0.3203 | 0.13 | 3500 | 0.1542 | 6.9560 | 6.9559 |
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+ | 0.2655 | 0.14 | 4000 | 0.1535 | 7.0848 | 7.0859 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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