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--- |
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license: cc-by-4.0 |
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base_model: kxx-kkk/FYP_sq2_mrqa_adqa_synqa |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: FYP_qa_final |
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results: |
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- task: |
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type: question-answering |
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name: Question Answering |
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dataset: |
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name: squad_v2 |
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type: squad_v2 |
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config: squad_v2 |
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split: validation |
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metrics: |
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- type: exact_match |
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value: 82.3 |
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name: Exact Match |
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- type: f1 |
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value: 85.7701063996245 |
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name: F1 |
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- task: |
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type: question-answering |
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name: Question Answering |
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dataset: |
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name: squad |
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type: squad |
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config: plain_text |
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split: validation |
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metrics: |
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- type: exact_match |
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value: 89.9 |
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name: Exact Match |
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- type: f1 |
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value: 93.57935153408677 |
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name: F1 |
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datasets: |
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- rajpurkar/squad_v2 |
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- mrqa |
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- UCLNLP/adversarial_qa |
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- mbartolo/synQA |
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language: |
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- en |
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pipeline_tag: question-answering |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# FYP_qa_final |
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This model is a fine-tuned version of [deepset/deberta-v3-base-squad2](https://huggingface.co/deepset/deberta-v3-base-squad2) on an [MRQA](https://huggingface.co/datasets/mrqa) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7493 |
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## Model description |
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This model is trained for performing extractive question-answering tasks for academic essays. |
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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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The dataset used for training is listed below according to training sequences: |
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1. [MRQA(train split)](https://huggingface.co/datasets/mrqa) |
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2. [UCLNLP/adversarial_qa](https://huggingface.co/datasets/UCLNLP/adversarial_qa) |
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3. [mbartolo/synQA](https://huggingface.co/datasets/mbartolo/synQA) |
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4. [MRQA(test split)](https://huggingface.co/datasets/mrqa)*This model |
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## Training procedure |
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The training approach uses the fine-tuning approach of transfer learning on the pre-trained model to perform NLP QA tasks. |
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Each time a model was trained with one dataset only and saved as the PTMs for the next training. |
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This model is the last model that trained with [MRQA(test split)](https://huggingface.co/datasets/mrqa). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.8084 | 0.48 | 300 | 3.1468 | |
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| 2.5707 | 0.96 | 600 | 2.9035 | |
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| 2.5187 | 1.44 | 900 | 2.7175 | |
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| 2.4463 | 1.91 | 1200 | 2.7497 | |
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| 2.4328 | 2.39 | 1500 | 2.7229 | |
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| 2.3839 | 2.87 | 1800 | 2.7493 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
