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End of training

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  1. README.md +26 -17
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -6,33 +6,34 @@ base_model: openai/whisper-tiny
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  tags:
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  - hf-asr-leaderboard
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  - generated_from_trainer
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- datasets:
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- - jpdiazpardo/guturalScream_metalVocals
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  model-index:
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- - name: "Whisper Tiny Metal - Juan Pablo D\xEDaz"
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  results: []
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  ---
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- # Whisper Tiny Metal - Juan Pablo Díaz
 
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- This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Gutural Scream & Metal Vocals dataset.
 
 
 
 
 
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  ## Model description
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- The model is inteded for automatic speech recognition in gutural and scream voice. The model was trained on vocals preprocessed using Spleeter source separtion algorithm.
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- ## Intended uses & limitations
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- Check out a demo of the model in my 'Spaces' repository: jpdiazpardo/jpdiazpardo-whisper-tiny-metal
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- Load the dataset from huggingface in your notebook:
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- ```python
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- from transformers import WhisperForConditionalGeneration, WhisperProcessor
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- model = WhisperForConditionalGeneration.from_pretrained("jpdiazpardo/whisper-tiny-metal")
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- processor = WhisperProcessor.from_pretrained("jpdiazpardo/whisper-tiny-metal")
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- ```
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  ## Training and evaluation data
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- jpdiazpardo/guturalScream_metalVocals
 
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  ## Training procedure
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@@ -45,11 +46,19 @@ The following hyperparameters were used during training:
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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: 1
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- - training_steps: 2
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  ### Training results
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  ### Framework versions
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  - Transformers 4.32.0
 
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  tags:
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  - hf-asr-leaderboard
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  - generated_from_trainer
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+ metrics:
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+ - wer
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  model-index:
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+ - name: Whisper Tiny Metal - Juan Pablo Diaz
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  results: []
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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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+ # Whisper Tiny Metal - Juan Pablo Diaz
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Gutural Scream and Metal Vocals dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6780
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+ - Wer: 79.9061
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  ## Model description
 
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+ More information needed
 
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+ ## Intended uses & limitations
 
 
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+ More information needed
 
 
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  ## Training and evaluation data
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+
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+ More information needed
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  ## Training procedure
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.0844 | 9.62 | 1000 | 1.3967 | 104.6055 |
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+ | 0.0018 | 19.23 | 2000 | 1.5861 | 93.5465 |
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+ | 0.0008 | 28.85 | 3000 | 1.6552 | 78.9381 |
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+ | 0.0006 | 38.46 | 4000 | 1.6780 | 79.9061 |
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+
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+
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  ### Framework versions
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  - Transformers 4.32.0
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