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README.md

@@ -1,68 +1,235 @@
 ---
-tags:
-- generated_from_trainer
-datasets:
-- squad_v2
+language: en
+license: mit
 model-index:
-- name: roberta-finetuned-squad_v2
-  results: []
+- name: roberta-finetuned
+  results:
+  - task:
+      type: question-answering
+    dataset:
+      name: SQuAD v2
+      type: squad_v2
+    metrics:
+    - type: Exact
+      value: 37.40419439063421
+    - type: F1
+      value: 40.42817816263742
+    - type: Total
+      value: 11873
+    - type: Hasans Exact
+      value: 72.58771929824562
+    - type: Hasans F1
+      value: 78.64435886049151
+    - type: Hasans Total
+      value: 5928
+    - type: Noans Exact
+      value: 2.3212783851976453
+    - type: Noans F1
+      value: 2.3212783851976453
+    - type: Noans Total
+      value: 5945
+    - type: Best Exact
+      value: 50.09685841825992
+    - type: Best Exact Thresh
+      value: 0.0
+    - type: Best F1
+      value: 50.09685841825992
+    - type: Best F1 Thresh
+      value: 0.0
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Model Card for Model ID
 
-# roberta-finetuned-squad_v2
+<!-- Provide a quick summary of what the model is/does. -->
 
-This model was trained from scratch on the squad_v2 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.9064
 
-## Model description
 
-More information needed
+## Model Details
 
-## Intended uses & limitations
+### Model Description
 
-More information needed
+<!-- Provide a longer summary of what this model is. -->
 
-## Training and evaluation data
 
-More information needed
 
-## Training procedure
+- **Developed by:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** en
+- **License:** mit
+- **Finetuned from model [optional]:** [More Information Needed]
 
-### Training hyperparameters
+### Model Sources [optional]
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 128
-- eval_batch_size: 128
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 512
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 1
+<!-- Provide the basic links for the model. -->
 
-### Training results
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 2.9129        | 0.2   | 100  | 1.4700          |
-| 1.4395        | 0.39  | 200  | 1.2407          |
-| 1.2356        | 0.59  | 300  | 1.0325          |
-| 1.1284        | 0.78  | 400  | 0.9750          |
-| 1.0821        | 0.98  | 500  | 0.9345          |
-| 0.9978        | 1.18  | 600  | 0.9893          |
-| 0.9697        | 1.37  | 700  | 0.9300          |
-| 0.9455        | 1.57  | 800  | 0.9351          |
-| 0.9322        | 1.76  | 900  | 0.9451          |
-| 0.9269        | 1.96  | 1000 | 0.9064          |
+## Uses
 
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Data Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
 
-### Framework versions
 
-- Transformers 4.34.1
-- Pytorch 2.1.0+cu118
-- Datasets 2.14.5
-- Tokenizers 0.14.1