Update README.md

README.md

@@ -1,76 +1,60 @@
 ---
 library_name: peft
 base_model: core42/jais-13b
+license: mit
+datasets:
+- arbml/Ashaar_dataset
+language:
+- ar
+metrics:
+- perplexity
+- bertscore
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+Fine-tuned using QLoRA for poem generation task.
 
 
-
-## Model Details
-
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [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]
+We utilize Ashaar dataset and fine-tune the model to generate poems.
 
-### Model Sources [optional]
+The input to the model is structred as follows:
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## 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
+\#\#\# Instruction: Generate a poem based on the following title, and the given era:
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+\#\#\# Input: \{Title of a poem + poet era\}
 
-[More Information Needed]
+\#\#\# Response: \{Poem verses\}
 
-### 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]
+- **Developed by:** Abdelrahman ’Boda’ Sadallah, Anastasiia Demidova, Daria Kotova
+- **Model type:** Causal LM
+- **Language(s) (NLP):** Arabic
+- **Finetuned from model [optional]:** core42/jais-13b
 
-### Out-of-Scope Use
+### Model Sources
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+- **Repository:** https://github.com/BodaSadalla98/llm-optimized-fintuning
 
-[More Information Needed]
+## Uses
 
-## Bias, Risks, and Limitations
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+The model is the result of our AI project. If you intend to use it, please, refer to the repo.
 
-[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
+For improving stories generation, you can play parameters: temeperature, top_p/top_k, repetition_penalty, etc.
 
-Use the code below to get started with the model.
-
-[More Information Needed]
 
 ## Training Details
 
@@ -78,26 +62,8 @@ Use the code below to get started with the model.
 
 <!-- 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]
-
+Link to the dataset on huggungface: https://huggingface.co/datasets/arbml/ashaar.
 
-#### 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
 
@@ -105,118 +71,21 @@ Use the code below to get started with the model.
 
 ### 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]
+Test split of the same dataset.
 
 #### Metrics
 
 <!-- These are the evaluation metrics being used, ideally with a description of why. -->
 
-[More Information Needed]
+We are using perplexity and BERTScore.
 
 ### 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]
-
-
-## Training procedure
-
-
-The following `bitsandbytes` quantization config was used during training:
-- quant_method: bitsandbytes
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: float16
-
-### Framework versions
+Perplexity: 48.3125
 
+BERTScore: 59.33
 
-- PEFT 0.6.0.dev0
 ## Training procedure
 
 
@@ -228,11 +97,11 @@ The following `bitsandbytes` quantization config was used during training:
 - llm_int8_skip_modules: None
 - llm_int8_enable_fp32_cpu_offload: False
 - llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: float16
+- bnb_4bit_quant_type: fp4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float32
 
 ### Framework versions
 
 
-- PEFT 0.6.0.dev0
+- PEFT 0.6.0.dev0