| --- |
| library_name: transformers |
| license: apache-2.0 |
| datasets: |
| - MENG21/studfacultyeval_dataset |
| language: |
| - tl |
| - en |
| metrics: |
| - accuracy |
| - f1 |
| - recall |
| - precision |
| pipeline_tag: text-classification |
| widget: |
| - text: laging pumapasok si sir! |
| example_title: Tagalog |
| - text: I really don't understand the lesson |
| example_title: English |
| - text: I love the way na magturo si sir, I always understand the lesson lagi |
| example_title: Tag-lish |
| --- |
| |
| # Model Card for Model ID |
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| <!-- Provide a quick summary of what the model is/does. --> |
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| ## Model Details |
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| ### Model Description |
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| <!-- Provide a longer summary of what this model is. --> |
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| This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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| - **Developed by:** Allan O. Ibo, Jr. |
| <!-- - **Funded by [optional]:** [More Information Needed] --> |
| <!-- - **Shared by [optional]:** [More Information Needed] --> |
| - **Model type:** Text Classification |
| - **Language(s) (NLP):** English/Tagalog |
| - **License:** Apache License |
| - **Finetuned from model [optional]:** BERT (Large) |
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| ### Model Sources [optional] |
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| <!-- Provide the basic links for the model. --> |
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| - **Repository:** [More Information Needed] |
| - **Paper [optional]:** [More Information Needed] |
| - **Demo [optional]:** [User Guide](https://huggingface.co/spaces/MENG21/studfacultyeval_prototype/blob/main/prototype-user-guide.pdf) |
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| ## Uses |
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| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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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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| <!-- <###################################################################> --> |
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| # results_bert-large-uncased |
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| This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2128 |
| - Accuracy: 0.9141 |
| - Precision: 0.9182 |
| - Recall: 0.9421 |
| - F1: 0.9300 |
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| ## Model description |
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| More information needed |
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| ## Intended uses & limitations |
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| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 1 |
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| ### Training results |
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| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.6415 | 0.09 | 50 | 0.5315 | 0.7175 | 0.6981 | 0.9394 | 0.8010 | |
| | 0.4007 | 0.18 | 100 | 0.7702 | 0.7243 | 0.9892 | 0.5505 | 0.7074 | |
| | 0.5158 | 0.28 | 150 | 0.4075 | 0.8591 | 0.8904 | 0.8748 | 0.8825 | |
| | 0.3934 | 0.37 | 200 | 0.2809 | 0.8763 | 0.9354 | 0.8546 | 0.8932 | |
| | 0.2691 | 0.46 | 250 | 0.3406 | 0.8832 | 0.8837 | 0.9294 | 0.9060 | |
| | 0.2814 | 0.55 | 300 | 0.2582 | 0.8768 | 0.8512 | 0.9651 | 0.9046 | |
| | 0.2735 | 0.64 | 350 | 0.2715 | 0.8953 | 0.8708 | 0.9711 | 0.9182 | |
| | 0.2411 | 0.74 | 400 | 0.2389 | 0.9103 | 0.9242 | 0.9279 | 0.9260 | |
| | 0.2371 | 0.83 | 450 | 0.2081 | 0.9104 | 0.9212 | 0.9316 | 0.9264 | |
| | 0.1974 | 0.92 | 500 | 0.2128 | 0.9141 | 0.9182 | 0.9421 | 0.9300 | |
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| ### Framework versions |
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| - Transformers 4.37.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
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| <!-- <###################################################################> --> |
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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] |
| - **Hours used:** [More Information Needed] |
| - **Cloud Provider:** [More Information Needed] |
| - **Compute Region:** [More Information Needed] |
| - **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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