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  ---
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- tags:
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- - generated_from_trainer
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- datasets:
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- - squad_v2
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  model-index:
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- - name: distilbert-finetuned-uncased-squad_v2
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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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- # distilbert-finetuned-uncased-squad_v2
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- This model was trained from scratch on the squad_v2 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 1.3930
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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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- More information needed
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- ## Training procedure
 
 
 
 
 
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- ### Training hyperparameters
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- The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 128
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- - eval_batch_size: 128
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- - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 512
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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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- - num_epochs: 4
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- ### Training results
 
 
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 3.6437 | 0.39 | 100 | 2.1780 |
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- | 2.1596 | 0.78 | 200 | 1.6557 |
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- | 1.8138 | 1.18 | 300 | 1.5683 |
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- | 1.6987 | 1.57 | 400 | 1.5076 |
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- | 1.6586 | 1.96 | 500 | 1.5350 |
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- | 1.5957 | 1.18 | 600 | 1.4431 |
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- | 1.5825 | 1.37 | 700 | 1.4955 |
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- | 1.5523 | 1.57 | 800 | 1.4444 |
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- | 1.5346 | 1.76 | 900 | 1.3930 |
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- | 1.5098 | 1.96 | 1000 | 1.4285 |
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- ### Framework versions
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- - Transformers 4.34.1
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- - Pytorch 2.1.0+cu118
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- - Datasets 2.14.5
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- - Tokenizers 0.14.1
 
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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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+ ### 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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+
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+ ### Direct Use
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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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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+
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+ ## Bias, Risks, and Limitations
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+
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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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+
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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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+
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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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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ #### Speeds, Sizes, Times [optional]
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+
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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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+
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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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+
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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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+ [More Information Needed]
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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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+ [More Information Needed]
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+ **APA:**
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+ [More Information Needed]
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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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+ [More Information Needed]
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+ ## Model Card Authors [optional]
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+ [More Information Needed]
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+ ## Model Card Contact
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+ [More Information Needed]
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