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library_name: transformers |
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tags: |
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- unsloth |
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--- |
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# Model Card for Model ID |
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Fine-tuned Mistral-7b specifically for evaluating IELTS essays with Direct Preference Optimization (DPO) |
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## Model Details |
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### Model Description |
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The model was fine-tuned using the QLoRA technique on a dataset of over 9,000 IELTS essay samples. QLoRA is a low-rank adaptation method that enables efficient fine-tuning of large language models while minimizing memory and compute requirements. The model was trained to predict essay scores based on the IELTS scoring rubric, which evaluates essays on four criteria: task achievement, coherence and cohesion, lexical resource, and grammatical range and accuracy. The model has been tested on a held-out set of essays and achieves strong performance, making it a useful tool for automated essay evaluation. To use the model, simply provide it with the text of an essay and it will output a predicted score between 0 and 9 for each of the four scoring criteria. |
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Uses: This model can be used by educators and students to evaluate the quality of IELTS essays and provide feedback on areas for improvement. It can also be used by test preparation companies to automatically score practice essays and provide students with instant feedback. |
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Limitations: While the model has been trained on a large dataset of IELTS essays, it may not perform as well on essays that are significantly different from those in the training set. Additionally, the model may not fully capture the nuances of human language and may occasionally make errors in scoring. It is recommended that the model be used as a tool to supplement human evaluation rather than as a replacement for it. |
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We hope you find this model useful for your IELTS essay evaluation needs! |
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- **Developed by:** Nguyen Minh Chi |
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- **Funded by [optional]:** Unsloth |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** 4-bit |
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- **Language(s) (NLP):** English |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** Mistral-7B |
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### Model Sources [optional] |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- 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. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Dataset Card if possible. --> |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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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). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
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