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--- |
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language: |
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- en |
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widget: |
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- text: "did abraham lincoln write the letter in saving private ryan <sep> In the 1998 war film Saving Private Ryan, General George Marshall (played by Harve Presnell) reads the Bixby letter to his officers before giving the order to find and send home Private James Francis Ryan after Ryan's three brothers died in battle." |
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example_title: "Bool QA" |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- google/boolq |
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metrics: |
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- accuracy |
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model-index: |
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- name: Bert Base Uncased Boolean Question Answer model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: boolq |
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type: google/boolq |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7149847094801223 |
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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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# Bert Base Uncased Boolean Question Answer model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the boolq dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1993 |
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- Accuracy: 0.7150 |
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## Model description |
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- **Model type:** Text Classification model |
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- **Language(s) (NLP):** English |
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- **License:** Apache 2.0 |
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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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- [Dataset](https://huggingface.co/datasets/google/boolq) |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.2317 | 0.9966 | 147 | 0.2198 | 0.6569 | |
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| 0.2 | 2.0 | 295 | 0.2002 | 0.6960 | |
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| 0.1741 | 2.9966 | 442 | 0.1968 | 0.7122 | |
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| 0.1469 | 3.9864 | 588 | 0.1993 | 0.7150 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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