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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cuad-qa |
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model-index: |
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- name: cuad_qa_model |
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results: [] |
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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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# cuad_qa_model |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the cuad-qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 56.3253 |
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- Jaccard: 0.1325 |
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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: 3 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 12 |
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- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
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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 | Jaccard | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 2931.2947 | 0.1075 | 100 | 125.3868 | 0.0261 | |
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| 114.0476 | 0.2149 | 200 | 98.0385 | 0.0225 | |
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| 92.3046 | 0.3224 | 300 | 86.1094 | 0.0279 | |
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| 83.4547 | 0.4299 | 400 | 80.0709 | 0.0403 | |
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| 80.4591 | 0.5373 | 500 | 75.2658 | 0.0433 | |
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| 76.238 | 0.6448 | 600 | 71.9617 | 0.0445 | |
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| 73.2576 | 0.7523 | 700 | 68.1718 | 0.0463 | |
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| 70.5061 | 0.8598 | 800 | 64.2118 | 0.0536 | |
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| 72.0594 | 0.9672 | 900 | 82.5902 | 0.0243 | |
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| 65.2249 | 1.0742 | 1000 | 59.8434 | 0.0647 | |
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| 63.2437 | 1.1816 | 1100 | 60.3719 | 0.0932 | |
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| 67.1502 | 1.2891 | 1200 | 63.5264 | 0.1114 | |
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| 65.1003 | 1.3966 | 1300 | 60.7845 | 0.1243 | |
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| 64.7538 | 1.5040 | 1400 | 66.3558 | 0.1200 | |
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| 66.7688 | 1.6115 | 1500 | 69.2212 | 0.1149 | |
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| 76.4721 | 1.7190 | 1600 | 69.5449 | 0.1458 | |
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| 82.2733 | 1.8264 | 1700 | 82.1182 | 0.0449 | |
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| 78.7475 | 1.9339 | 1800 | 62.4942 | 0.1581 | |
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| 69.5967 | 2.0408 | 1900 | 63.3104 | 0.1507 | |
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| 67.6753 | 2.1483 | 2000 | 56.4553 | 0.2238 | |
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| 64.0365 | 2.2558 | 2100 | 60.3552 | 0.1978 | |
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| 62.561 | 2.3632 | 2200 | 55.5222 | 0.2238 | |
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| 62.0848 | 2.4707 | 2300 | 51.5148 | 0.2239 | |
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| 59.3192 | 2.5782 | 2400 | 56.1338 | 0.1939 | |
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| 63.3072 | 2.6857 | 2500 | 55.3624 | 0.2385 | |
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| 63.0132 | 2.7931 | 2600 | 48.8478 | 0.2614 | |
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| 61.0742 | 2.9006 | 2700 | 57.2687 | 0.2574 | |
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| 63.7064 | 3.0075 | 2800 | 58.7552 | 0.2569 | |
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| 61.3371 | 3.1150 | 2900 | 62.7214 | 0.2473 | |
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| 66.2795 | 3.2225 | 3000 | 60.0179 | 0.2640 | |
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| 65.9729 | 3.3299 | 3100 | 59.7260 | 0.2879 | |
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| 67.5846 | 3.4374 | 3200 | 63.1864 | 0.2627 | |
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| 65.6924 | 3.5449 | 3300 | 58.8332 | 0.2743 | |
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| 64.2456 | 3.6523 | 3400 | 59.7355 | 0.1667 | |
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| 64.9793 | 3.7598 | 3500 | 57.0126 | 0.1622 | |
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| 63.8452 | 3.8673 | 3600 | 56.8423 | 0.1332 | |
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| 65.2058 | 3.9747 | 3700 | 56.3253 | 0.1325 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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