Tillicollaps/Gender-Classification-russian-name

1---2library_name: transformers3language:4- ru5pipeline_tag: text-classification6---7 8 9 10### Model Description11 12<!-- Provide a longer summary of what this model is. -->13This model is a finely tuned version of padmajabfrl/Gender-Classification. The dataset consists of 26,000 lines.14"loss": 0.002415 16- **Developed by:** Tillicollaps17- **Language(s) (NLP):** russian18 19## Uses20 21from transformers import AutoTokenizer, AutoModelForSequenceClassification22from transformers import TextClassificationPipeline,23from transliterate import translit24 25tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased")26 27model = AutoModelForSequenceClassification.from_pretrained("CustomModel_Russia", num_labels=2) 28 29nlp = TextClassificationPipeline(model=model, tokenizer=tokenizer)30 31#If the language of the text is different from English, use the 'translit' library.32 33name = "Cтанислав"34 35tran = translit(name, language_code='ru', reversed=True)36 37result = nlp(tran) 38 39 40<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->41 42### Direct Use43 44<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->45 46[More Information Needed]47 48### Downstream Use [optional]49 50<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->51 52[More Information Needed]53 54### Out-of-Scope Use55 56<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->57 58[More Information Needed]59 60## Bias, Risks, and Limitations61 62<!-- This section is meant to convey both technical and sociotechnical limitations. -->63 64[More Information Needed]65 66### Recommendations67 68<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->69 70Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.71 72## How to Get Started with the Model73 74Use the code below to get started with the model.75 76[More Information Needed]77 78## Training Details79 80### Training Data81 82<!-- This should link to a Dataset 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. -->83 84[More Information Needed]85 86### Training Procedure87 88<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->89 90#### Preprocessing [optional]91 92[More Information Needed]93 94 95#### Training Hyperparameters96 97- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->98 99#### Speeds, Sizes, Times [optional]100 101<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->102 103[More Information Needed]104 105## Evaluation106 107<!-- This section describes the evaluation protocols and provides the results. -->108 109### Testing Data, Factors & Metrics110 111#### Testing Data112 113<!-- This should link to a Dataset Card if possible. -->114 115[More Information Needed]116 117#### Factors118 119<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->120 121[More Information Needed]122 123#### Metrics124 125<!-- These are the evaluation metrics being used, ideally with a description of why. -->126 127[More Information Needed]128 129### Results130 131[More Information Needed]132 133#### Summary134 135 136 137## Model Examination [optional]138 139<!-- Relevant interpretability work for the model goes here -->140 141[More Information Needed]142 143## Environmental Impact144 145<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->146 147Carbon 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).148 149- **Hardware Type:** [More Information Needed]150- **Hours used:** [More Information Needed]151- **Cloud Provider:** [More Information Needed]152- **Compute Region:** [More Information Needed]153- **Carbon Emitted:** [More Information Needed]154 155## Technical Specifications [optional]156 157### Model Architecture and Objective158 159[More Information Needed]160 161### Compute Infrastructure162 163[More Information Needed]164 165#### Hardware166 167[More Information Needed]168 169#### Software170 171[More Information Needed]172 173## Citation [optional]174 175<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->176 177**BibTeX:**178 179[More Information Needed]180 181**APA:**182 183[More Information Needed]184 185## Glossary [optional]186 187<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->188 189[More Information Needed]190 191## More Information [optional]192 193[More Information Needed]194 195## Model Card Authors [optional]196 197[More Information Needed]198 199## Model Card Contact200 201[More Information Needed]