Create README.md

README.md

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+---
+language:
+- en
+- fr
+- de
+- ru
+- ar
+metrics:
+- f1
+- accuracy
+- precision
+- recall
+library_name: transformers
+---
+# Your Model Name
+**Fine_Tuned_HF_Language_Identification_Model:** Language Identification Model
+
+## Description
+This model is a language identification model that can classify text into different languages. It has been fine-tuned to identify languages such as English, French, German, Arabic, and Russian. This model is built on the XLM-RoBERTa architecture and is capable of achieving high accuracy in language identification tasks.
+
+## Model Details
+- Base Model: XLM-RoBERTa
+- Fine-Tuning: The model has been fine-tuned for language identification using a custom dataset containing text samples in various languages.
+- Evaluation Metrics: The model's performance is assessed using accuracy and F1-score for both per-language and overall model performance.
+
+## Training Data
+The model has been trained on a dataset that includes text samples from different languages, including English, French, German, Arabic, and Russian. The training data sources include a variety of texts, documents, and web content in these languages.
+
+## Usage
+To use this model for language identification, you can follow these steps:
+
+1. Install the necessary libraries and dependencies.
+2. Load the pre-trained model using the provided model checkpoint.
+3. Tokenize the input text using the model's tokenizer.
+4. Make predictions on the tokenized input to identify the language.
+
+