finetuned lora model v2

README.md

@@ -1,99 +1,202 @@
 ---
 library_name: peft
 base_model: xlm-roberta-base
-license: mit
-language:
-- am
-metrics:
-- accuracy
-- f1
-pipeline_tag: text-classification
 ---
 
-# xlm-roberta-base-lora-amharic-news-classification
+# Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-This repo contains LoRA adapters for the [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) model finetuned on the [Amharic-News-Text-classification-Dataset](https://huggingface.co/datasets/israel/Amharic-News-Text-classification-Dataset).
 
-The finetuned model classifies an Amharic news article into one of the following 6 categories.
-- ሀገር አቀፍ ዜና (Local News)
-- መዝናኛ (Entertainment)
-- ስፖርት (Sports)
-- ቢዝነስ (Business)
-- ዓለም አቀፍ ዜና (International News)
-- ፖለቲካ (Politics)
 
-It achieves the following results on the evaluation set:
-- Train Loss: **0.3447**
-- Validation Loss: **0.3947**
-- Validation Accuracy: **0.8541**
-- Validation F1 Score (macro): **0.8105**
-- Validation F1 Score (weighted): **0.8551**
 
-## How to use
+## Model Details
 
-You can use this model with a pipeline for text classification. 
-But first, you need to install the `peft` library like so: 
+### Model Description
 
-```console 
-pip install peft
-```
+<!-- Provide a longer summary of what this model is. -->
 
-Then, you can run the following code.
 
-```python
-from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 
-model_id = "xlm-roberta-base"
-peft_model_id = "rasyosef/xlm-roberta-base-lora-amharic-news-classification" 
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
 
-categories = ['ሀገር አቀፍ ዜና', 'መዝናኛ', 'ስፖርት', 'ቢዝነስ', 'ዓለም አቀፍ ዜና', 'ፖለቲካ']
-id2label = {i: lbl for i, lbl in enumerate(categories)}
-label2id = {lbl: i for i, lbl in enumerate(categories)}
+### Model Sources [optional]
 
-tokenizer = AutoTokenizer.from_pretrained(model_id)
+<!-- Provide the basic links for the model. -->
 
-model = AutoModelForSequenceClassification.from_pretrained(
-    model_id, 
-    num_labels=len(categories), # 6
-    id2label=id2label,
-    label2id=label2id
-)
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-model.load_adapter(peft_model_id)
+## Uses
 
-classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-classifier([
-  """ቅርሶቹን ለመታደግ የተጀመረው የሙዚዬም ግንባታም በበጀት ምክንያት ተቋርጧል።
-  
-  በአፄ ቴዎድሮስ የንግስና ቦታ ደረስጌ ማሪያም ተጀምሮ የቆመው የሙዚየሙ ግንባታ ተጠናቀቆ ስራ 
-  እንዲጀምር ነዋሪዎች ጠይቀዋል። ዘመነ መሳፍንት መቋጫ ያገኘባት የኢትዮጵያ አንድነት የታወጀባት ዳግማዊ 
-  አፄ ቴዎድሮስ ከመንገሳቸው በፊት ደጃች ውቤን ቧሂት ከሚባል ቦታ ድል አድርገው ደጃች ውቤ ለንግስና ባዘጋጁት የንግስና ቦታና 
-  እቃዎች ንጉሰ ነገስት ዘኢትዮጵያ ተብለው የነገሱባት ቦታ ናት።""", # 'ሀገር አቀፍ ዜና'
-])
-```
+### Direct Use
 
-Output:
-```python
-[{'label': 'ሀገር አቀፍ ዜና', 'score': 0.977573037147522}]
-```
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-## Model Details
+[More Information Needed]
 
-### Model Description
+### Downstream Use [optional]
 
-<!-- Provide a longer summary of what this model is. -->
+<!-- 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
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+<!-- 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 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. -->
+
+[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 Dataset 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

adapter_model.safetensors

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