rambaldi47 commited on
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End of training

Browse files
README.md CHANGED
@@ -5,24 +5,9 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - PolyAI/minds14
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- metrics:
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- - wer
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  model-index:
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  - name: whisper-tiny
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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: PolyAI/minds14
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- type: PolyAI/minds14
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- config: en-US
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- split: train
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- args: en-US
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- metrics:
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- - name: Wer
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- type: wer
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- value: 0.6770956316410862
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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
@@ -31,10 +16,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # whisper-tiny
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.7268
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- - Wer Ortho: 0.6798
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- - Wer: 0.6771
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  ## Model description
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@@ -53,21 +34,18 @@ More information needed
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  ### Training hyperparameters
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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: 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: 500
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  - mixed_precision_training: Native AMP
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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- | 0.0014 | 17.86 | 500 | 0.7268 | 0.6798 | 0.6771 |
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  ### Framework versions
 
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  - generated_from_trainer
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  datasets:
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  - PolyAI/minds14
 
 
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  model-index:
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  - name: whisper-tiny
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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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  # whisper-tiny
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  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
 
 
 
 
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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  - train_batch_size: 16
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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: 200
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  - mixed_precision_training: Native AMP
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  ### Training results
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  ### Framework versions
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