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  ---
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- language: en
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- license: mit
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- model-index:
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- - name: distilbert-finetuned-uncased
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- results:
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- - task:
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- type: question-answering
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- dataset:
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- name: SQuAD v2
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- type: squad_v2
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- metrics:
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- - type: Exact
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- value: 23.347090036216628
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- - type: F1
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- value: 26.869992349988973
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- - type: Total
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- value: 11873
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- - type: Hasans Exact
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- value: 38.630229419703106
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- - type: Hasans F1
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- value: 45.686136837283904
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- - type: Hasans Total
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- value: 5928
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- - type: Noans Exact
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- value: 8.107653490328007
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- - type: Noans F1
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- value: 8.107653490328007
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- - type: Noans Total
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- value: 5945
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- - type: Best Exact
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- value: 50.11370336056599
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- - type: Best Exact Thresh
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- value: 0.0
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- - type: Best F1
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- value: 50.11370336056599
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- - type: Best F1 Thresh
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- value: 0.0
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- - **Developed by:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** en
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- - **License:** mit
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- - **Finetuned from model [optional]:** [More Information Needed]
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-
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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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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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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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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- <!-- 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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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Data Card if possible. -->
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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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- [More Information Needed]
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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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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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- ### Compute Infrastructure
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- [More Information Needed]
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- #### Hardware
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- #### Software
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- [More Information Needed]
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- ## Citation [optional]
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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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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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+ {}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ ---
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+ language: en
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+ license: mit
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+ ---
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+
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+ # distilbert-finetuned-uncased Model
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+ This model is fine-tuned on the SQuAD v2 dataset for the task of question answering.
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+
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+ ## Training Procedure
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+ - Number of Epochs: 4
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+ - Learning Rate: 2e-05
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+ - Batch Size: 128 (per device)
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+ - Evaluation Strategy: Every 100 steps
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+ - Save Strategy: Every 100 steps
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+ - FP16 Training: Yes
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+
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+ ## Evaluation Results
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+ - Exact Match: 23.347090036216628
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+ - F1 Score: 26.869992349988973
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+ - Total: 11873
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+ - Has Answer Exact: 38.630229419703106
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+ - Has Answer F1: 45.686136837283904
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+ - Has Answer Total: 5928
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+ - No Answer Exact: 8.107653490328007
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+ - No Answer F1: 8.107653490328007
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+ - No Answer Total: 5945
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+ - Best Exact: 50.11370336056599
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+ - Best Exact Threshold: 0.0
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+ - Best F1: 50.11370336056599
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+ - Best F1 Threshold: 0.0
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+