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@@ -66,8 +66,6 @@ This model is built for phoneme recognition tasks. It was developed by fine-tuni
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  Evaluate the model's performance for your specific use case.
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  ## How to Get Started with the Model
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  #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
 
 
 
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  #### Speeds, Sizes, Times [optional]
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- Training dataset consists of samples from 2 to 30 seconds.
 
 
 
 
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  <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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  [More Information Needed]
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  #### Testing Data
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- The model was evaluated on TIMIT's test split
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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  #### Metrics
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  <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- PER (Phoneme Error Rate) on TIMIT's test split:
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  ### Results
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- [More Information Needed]
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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  ## Environmental Impact
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  <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
 
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  [More Information Needed]
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  **APA:**
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- [More Information Needed]
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  ## Model Card Authors [optional]
 
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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  Evaluate the model's performance for your specific use case.
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  ## How to Get Started with the Model
 
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  #### Training Hyperparameters
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+ **Training regime:**
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+ - learning rate: 1e-5
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+ - optimizer: AdamW
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+ - batch size: 64
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+ - weight decay: 0.001
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+ - epochs: 50
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  #### Speeds, Sizes, Times [optional]
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+ Avg epoch training time: 650s
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+ Number of updates: 36050
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+ Final training loss:
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+ Final validation loss:
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  <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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  [More Information Needed]
 
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  #### Testing Data
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+ The model was evaluated on TIMIT's test split.
 
 
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  #### Metrics
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  <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+ CER/PER (Phoneme Error Rate)
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  ### Results
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+ PER (Phoneme Error Rate) on TIMIT's test split: 0.0416
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  ## Environmental Impact
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  <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+ <!-- **BibTeX:**
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  [More Information Needed]
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  **APA:**
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+ [More Information Needed] -->
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  ## Model Card Authors [optional]