Create README.md

README.md

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+# Model Card for t5-small-spoken-typo
+
+<!-- Provide a quick summary of what the model is/does. [Optional] -->
+This is a finetuned t5-small model using Spoken corpora (DailyDialog and BNC). We have done a number of things to the data though
+- Only used sentences of 2-5 words long 
+- Removed apostrophes, commas etc
+- Added in typos across the data set
+- And most importantly - removed spaces
+
+## Task
+The primary task of this model is **Text Correction**, specifically designed for:
+
+- **Sentence Correction**: Correcting sentences with missing spaces or typographical errors to enhance readability and understanding. This task is crucial for applications like assistive technology tools, text preprocessing in NLP pipelines, and improving user-generated content.
+
+- **Text Normalization**: Converting informal or irregular text forms into a more standard, grammatically correct format. This includes expanding contractions (e.g., turning &#34;whatsup&#34; into &#34;what&#39;s up&#34;), fixing common misspellings, and ensuring consistent use of language.
+
+This model is particularly suited for processing user-generated content where informal language, abbreviations, and typos are common. It aims to improve the clarity and quality of text inputs, making them more accessible for subsequent NLP tasks or human readers.
+
+
+
+
+
+#  Table of Contents
+
+- [Model Card for t5-small-spoken-typo](#model-card-for--model_id-)
+- [Table of Contents](#table-of-contents)
+- [Table of Contents](#table-of-contents-1)
+- [Model Details](#model-details)
+  - [Model Description](#model-description)
+- [Uses](#uses)
+  - [Direct Use](#direct-use)
+  - [Downstream Use [Optional]](#downstream-use-optional)
+  - [Out-of-Scope Use](#out-of-scope-use)
+- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
+  - [Recommendations](#recommendations)
+- [Training Details](#training-details)
+  - [Training Data](#training-data)
+  - [Training Procedure](#training-procedure)
+    - [Preprocessing](#preprocessing)
+    - [Speeds, Sizes, Times](#speeds-sizes-times)
+- [Evaluation](#evaluation)
+  - [Testing Data, Factors & Metrics](#testing-data-factors--metrics)
+    - [Testing Data](#testing-data)
+    - [Factors](#factors)
+    - [Metrics](#metrics)
+  - [Results](#results)
+- [Model Examination](#model-examination)
+- [Environmental Impact](#environmental-impact)
+- [Technical Specifications [optional]](#technical-specifications-optional)
+  - [Model Architecture and Objective](#model-architecture-and-objective)
+  - [Compute Infrastructure](#compute-infrastructure)
+    - [Hardware](#hardware)
+    - [Software](#software)
+- [Citation](#citation)
+- [Glossary [optional]](#glossary-optional)
+- [More Information [optional]](#more-information-optional)
+- [Model Card Authors [optional]](#model-card-authors-optional)
+- [Model Card Contact](#model-card-contact)
+- [How to Get Started with the Model](#how-to-get-started-with-the-model)
+
+
+# Model Details
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+This is a finetuned t5-small model using Spoken corpora (DailyDialog and BNC). We have done a number of things to the data though
+- Only used sentences of 2-5 words long 
+- Removed apostrophes, commas etc
+- Added in typos across the data set
+- And most importantly - removed spaces
+
+## Task
+The primary task of this model is **Text Correction**, specifically designed for:
+
+- **Sentence Correction**: Correcting sentences with missing spaces or typographical errors to enhance readability and understanding. This task is crucial for applications like assistive technology tools, text preprocessing in NLP pipelines, and improving user-generated content.
+
+- **Text Normalization**: Converting informal or irregular text forms into a more standard, grammatically correct format. This includes expanding contractions (e.g., turning &#34;whatsup&#34; into &#34;what&#39;s up&#34;), fixing common misspellings, and ensuring consistent use of language.
+
+This model is particularly suited for processing user-generated content where informal language, abbreviations, and typos are common. It aims to improve the clarity and quality of text inputs, making them more accessible for subsequent NLP tasks or human readers.
+
+
+- **Developed by:** More information needed
+- **Shared by [Optional]:** More information needed
+- **Model type:** Language model
+- **Language(s) (NLP):** en
+- **License:** apache-2.0
+- **Parent Model:** More information needed
+- **Resources for more information:** More information needed
+    - [GitHub Repo](https://github.com/willwade/dailyDialogCorrections/)
+
+
+# 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. -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info 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 -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
+ 
+
+
+
+## Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
+
+
+
+
+# Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+
+
+## Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+
+
+
+
+# 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 on training data 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
+
+More information needed
+
+### Speeds, Sizes, Times
+
+<!-- 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
+
+# Model Examination
+
+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:** 0.41
+
+# Technical Specifications [optional]
+
+## Model Architecture and Objective
+
+More information needed
+
+## Compute Infrastructure
+
+More information needed
+
+### Hardware
+
+More information needed
+
+### Software
+
+More information needed
+
+# Citation
+
+<!-- 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]
+
+<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
+
+Will Wade
+
+# Model Card Contact
+
+More information needed
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+<details>
+<summary> Click to expand </summary>
+
+More information needed
+
+</details>