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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- squad_v2 |
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model-index: |
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- name: bert-finetuned-uncased-squad_v2 |
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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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split: validation |
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metrics: |
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- type: exact |
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value: 100.0 |
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name: Exact |
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- type: f1 |
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value: 100.0 |
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name: F1 |
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- type: total |
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value: 2 |
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name: Total |
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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-finetuned-uncased-squad_v2 |
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This model was trained from scratch on the squad_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1459 |
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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: |
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- learning_rate: 2e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.2307 | 0.2 | 100 | 1.8959 | |
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| 1.9581 | 0.39 | 200 | 1.4856 | |
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| 1.6358 | 0.59 | 300 | 1.3948 | |
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| 1.4964 | 0.78 | 400 | 1.2934 | |
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| 1.4169 | 0.98 | 500 | 1.2605 | |
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| 1.327 | 1.18 | 600 | 1.2218 | |
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| 1.2763 | 1.37 | 700 | 1.2539 | |
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| 1.2755 | 1.57 | 800 | 1.2090 | |
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| 1.251 | 1.76 | 900 | 1.2041 | |
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| 1.229 | 1.96 | 1000 | 1.2159 | |
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| 1.1921 | 2.16 | 1100 | 1.1828 | |
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| 1.1926 | 2.35 | 1200 | 1.2120 | |
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| 1.1606 | 2.55 | 1300 | 1.1737 | |
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| 1.1486 | 2.75 | 1400 | 1.1469 | |
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| 1.1195 | 2.94 | 1500 | 1.1459 | |
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| 1.0883 | 3.14 | 1600 | 1.1570 | |
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| 1.0526 | 3.33 | 1700 | 1.1771 | |
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| 1.0611 | 3.53 | 1800 | 1.1740 | |
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| 1.0521 | 3.73 | 1900 | 1.1596 | |
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| 1.0476 | 3.92 | 2000 | 1.1538 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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