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bert-soccer-qa

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-4.0
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+ base_model: deepset/bert-base-uncased-squad2
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: bert-soccer-qa
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+ results: []
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+ ---
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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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+
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+ # bert-soccer-qa
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+
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+ This model is a fine-tuned version of [deepset/bert-base-uncased-squad2](https://huggingface.co/deepset/bert-base-uncased-squad2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3943
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+ - Exact: 74.5971
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+ - F1: 80.7187
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+ - Total: 25690
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+ - Hasans Exact: 74.5971
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+ - Hasans F1: 80.7187
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+ - Hasans Total: 25690
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+ - Best Exact: 74.5971
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+ - Best Exact Thresh: 0.0
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+ - Best F1: 80.7187
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+ - Best F1 Thresh: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Exact | F1 | Total | Hasans Exact | Hasans F1 | Hasans Total | Best Exact | Best Exact Thresh | Best F1 | Best F1 Thresh |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-----:|:------------:|:---------:|:------------:|:----------:|:-----------------:|:-------:|:--------------:|
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+ | 0.9455 | 0.0155 | 100 | 0.8127 | 69.8521 | 77.1360 | 25690 | 69.8521 | 77.1360 | 25690 | 69.8521 | 0.0 | 77.1360 | 0.0 |
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+ | 0.8743 | 0.0311 | 200 | 0.7383 | 70.2141 | 77.3821 | 25690 | 70.2141 | 77.3821 | 25690 | 70.2141 | 0.0 | 77.3821 | 0.0 |
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+ | 0.7189 | 0.0466 | 300 | 0.7195 | 71.0393 | 78.0890 | 25690 | 71.0393 | 78.0890 | 25690 | 71.0393 | 0.0 | 78.0890 | 0.0 |
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+ | 0.7367 | 0.0622 | 400 | 0.6836 | 71.0899 | 78.0062 | 25690 | 71.0899 | 78.0062 | 25690 | 71.0899 | 0.0 | 78.0062 | 0.0 |
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+ | 0.6469 | 0.0777 | 500 | 0.6646 | 71.4247 | 78.2333 | 25690 | 71.4247 | 78.2333 | 25690 | 71.4247 | 0.0 | 78.2333 | 0.0 |
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+ | 0.6657 | 0.0932 | 600 | 0.6493 | 70.2842 | 77.1248 | 25690 | 70.2842 | 77.1248 | 25690 | 70.2842 | 0.0 | 77.1248 | 0.0 |
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+ | 0.662 | 0.1088 | 700 | 0.6340 | 72.2265 | 79.0144 | 25690 | 72.2265 | 79.0144 | 25690 | 72.2265 | 0.0 | 79.0144 | 0.0 |
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+ | 0.6969 | 0.1243 | 800 | 0.6086 | 72.1292 | 78.8389 | 25690 | 72.1292 | 78.8389 | 25690 | 72.1292 | 0.0 | 78.8389 | 0.0 |
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+ | 0.669 | 0.1398 | 900 | 0.5938 | 71.8957 | 78.6137 | 25690 | 71.8957 | 78.6137 | 25690 | 71.8957 | 0.0 | 78.6137 | 0.0 |
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+ | 0.6676 | 0.1554 | 1000 | 0.5817 | 72.2849 | 78.8877 | 25690 | 72.2849 | 78.8877 | 25690 | 72.2849 | 0.0 | 78.8877 | 0.0 |
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+ | 0.6664 | 0.1709 | 1100 | 0.5696 | 71.9541 | 78.6815 | 25690 | 71.9541 | 78.6815 | 25690 | 71.9541 | 0.0 | 78.6815 | 0.0 |
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+ | 0.6006 | 0.1865 | 1200 | 0.5661 | 72.0631 | 78.7534 | 25690 | 72.0631 | 78.7534 | 25690 | 72.0631 | 0.0 | 78.7534 | 0.0 |
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+ | 0.6111 | 0.2020 | 1300 | 0.5587 | 72.6586 | 79.2351 | 25690 | 72.6586 | 79.2351 | 25690 | 72.6586 | 0.0 | 79.2351 | 0.0 |
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+ | 0.5793 | 0.2175 | 1400 | 0.5600 | 72.3939 | 79.0052 | 25690 | 72.3939 | 79.0052 | 25690 | 72.3939 | 0.0 | 79.0052 | 0.0 |
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+ | 0.6064 | 0.2331 | 1500 | 0.5501 | 72.7443 | 79.3616 | 25690 | 72.7443 | 79.3616 | 25690 | 72.7443 | 0.0 | 79.3616 | 0.0 |
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+ | 0.6314 | 0.2486 | 1600 | 0.5354 | 72.2772 | 78.8176 | 25690 | 72.2772 | 78.8176 | 25690 | 72.2772 | 0.0 | 78.8176 | 0.0 |
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+ | 0.6741 | 0.2641 | 1700 | 0.5330 | 72.1059 | 78.6777 | 25690 | 72.1059 | 78.6777 | 25690 | 72.1059 | 0.0 | 78.6777 | 0.0 |
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+ | 0.5912 | 0.2797 | 1800 | 0.5291 | 72.2499 | 78.7891 | 25690 | 72.2499 | 78.7891 | 25690 | 72.2499 | 0.0 | 78.7891 | 0.0 |
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+ | 0.584 | 0.2952 | 1900 | 0.5198 | 72.5691 | 79.1296 | 25690 | 72.5691 | 79.1296 | 25690 | 72.5691 | 0.0 | 79.1296 | 0.0 |
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+ | 0.64 | 0.3108 | 2000 | 0.5117 | 72.7910 | 79.2873 | 25690 | 72.7910 | 79.2873 | 25690 | 72.7910 | 0.0 | 79.2873 | 0.0 |
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+ | 0.5361 | 0.3263 | 2100 | 0.5079 | 73.1335 | 79.6027 | 25690 | 73.1335 | 79.6027 | 25690 | 73.1335 | 0.0 | 79.6027 | 0.0 |
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+ | 0.5935 | 0.3418 | 2200 | 0.5025 | 72.9350 | 79.4924 | 25690 | 72.9350 | 79.4924 | 25690 | 72.9350 | 0.0 | 79.4924 | 0.0 |
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+ | 0.5198 | 0.3574 | 2300 | 0.4996 | 72.6975 | 79.2533 | 25690 | 72.6975 | 79.2533 | 25690 | 72.6975 | 0.0 | 79.2533 | 0.0 |
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+ | 0.5474 | 0.3729 | 2400 | 0.4912 | 73.2970 | 79.7562 | 25690 | 73.2970 | 79.7562 | 25690 | 73.2970 | 0.0 | 79.7562 | 0.0 |
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+ | 0.5655 | 0.3884 | 2500 | 0.4847 | 73.4605 | 79.9581 | 25690 | 73.4605 | 79.9581 | 25690 | 73.4605 | 0.0 | 79.9581 | 0.0 |
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+ | 0.5652 | 0.4040 | 2600 | 0.4784 | 73.3320 | 79.8207 | 25690 | 73.3320 | 79.8207 | 25690 | 73.3320 | 0.0 | 79.8207 | 0.0 |
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+ | 0.5288 | 0.4195 | 2700 | 0.4846 | 73.4838 | 79.9261 | 25690 | 73.4838 | 79.9261 | 25690 | 73.4838 | 0.0 | 79.9261 | 0.0 |
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+ | 0.539 | 0.4351 | 2800 | 0.4739 | 73.0790 | 79.5401 | 25690 | 73.0790 | 79.5401 | 25690 | 73.0790 | 0.0 | 79.5401 | 0.0 |
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+ | 0.5493 | 0.4506 | 2900 | 0.4694 | 73.3009 | 79.6920 | 25690 | 73.3009 | 79.6920 | 25690 | 73.3009 | 0.0 | 79.6920 | 0.0 |
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+ | 0.4785 | 0.4661 | 3000 | 0.4669 | 73.9432 | 80.1966 | 25690 | 73.9432 | 80.1966 | 25690 | 73.9432 | 0.0 | 80.1966 | 0.0 |
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+ | 0.4979 | 0.4817 | 3100 | 0.4644 | 73.5189 | 79.8528 | 25690 | 73.5189 | 79.8528 | 25690 | 73.5189 | 0.0 | 79.8528 | 0.0 |
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+ | 0.4908 | 0.4972 | 3200 | 0.4576 | 73.5734 | 79.9085 | 25690 | 73.5734 | 79.9085 | 25690 | 73.5734 | 0.0 | 79.9085 | 0.0 |
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+ | 0.4845 | 0.5127 | 3300 | 0.4491 | 73.8147 | 80.1410 | 25690 | 73.8147 | 80.1410 | 25690 | 73.8147 | 0.0 | 80.1410 | 0.0 |
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+ | 0.5234 | 0.5283 | 3400 | 0.4499 | 73.6006 | 79.9882 | 25690 | 73.6006 | 79.9882 | 25690 | 73.6006 | 0.0 | 79.9882 | 0.0 |
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+ | 0.5345 | 0.5438 | 3500 | 0.4415 | 73.6395 | 79.9724 | 25690 | 73.6395 | 79.9724 | 25690 | 73.6395 | 0.0 | 79.9724 | 0.0 |
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+ | 0.5153 | 0.5594 | 3600 | 0.4388 | 73.5228 | 79.8471 | 25690 | 73.5228 | 79.8471 | 25690 | 73.5228 | 0.0 | 79.8471 | 0.0 |
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+ | 0.5113 | 0.5749 | 3700 | 0.4451 | 73.9393 | 80.2260 | 25690 | 73.9393 | 80.2260 | 25690 | 73.9393 | 0.0 | 80.2260 | 0.0 |
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+ | 0.4752 | 0.5904 | 3800 | 0.4427 | 73.7330 | 80.0047 | 25690 | 73.7330 | 80.0047 | 25690 | 73.7330 | 0.0 | 80.0047 | 0.0 |
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+ | 0.5161 | 0.6060 | 3900 | 0.4382 | 73.7018 | 79.9274 | 25690 | 73.7018 | 79.9274 | 25690 | 73.7018 | 0.0 | 79.9274 | 0.0 |
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+ | 0.4734 | 0.6215 | 4000 | 0.4380 | 73.8887 | 80.0773 | 25690 | 73.8887 | 80.0773 | 25690 | 73.8887 | 0.0 | 80.0773 | 0.0 |
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+ | 0.4852 | 0.6370 | 4100 | 0.4334 | 74.0093 | 80.1717 | 25690 | 74.0093 | 80.1717 | 25690 | 74.0093 | 0.0 | 80.1717 | 0.0 |
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+ | 0.5121 | 0.6526 | 4200 | 0.4244 | 73.9471 | 80.1321 | 25690 | 73.9471 | 80.1321 | 25690 | 73.9471 | 0.0 | 80.1321 | 0.0 |
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+ | 0.4475 | 0.6681 | 4300 | 0.4285 | 73.9782 | 80.1311 | 25690 | 73.9782 | 80.1311 | 25690 | 73.9782 | 0.0 | 80.1311 | 0.0 |
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+ | 0.4963 | 0.6837 | 4400 | 0.4176 | 74.0016 | 80.1124 | 25690 | 74.0016 | 80.1124 | 25690 | 74.0016 | 0.0 | 80.1124 | 0.0 |
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+ | 0.478 | 0.6992 | 4500 | 0.4187 | 74.2857 | 80.3374 | 25690 | 74.2857 | 80.3374 | 25690 | 74.2857 | 0.0 | 80.3374 | 0.0 |
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+ | 0.4634 | 0.7147 | 4600 | 0.4158 | 74.0171 | 80.1405 | 25690 | 74.0171 | 80.1405 | 25690 | 74.0171 | 0.0 | 80.1405 | 0.0 |
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+ | 0.4562 | 0.7303 | 4700 | 0.4158 | 74.0444 | 80.1174 | 25690 | 74.0444 | 80.1174 | 25690 | 74.0444 | 0.0 | 80.1174 | 0.0 |
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+ | 0.509 | 0.7458 | 4800 | 0.4160 | 73.9081 | 79.9863 | 25690 | 73.9081 | 79.9863 | 25690 | 73.9081 | 0.0 | 79.9863 | 0.0 |
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+ | 0.5062 | 0.7613 | 4900 | 0.4129 | 74.0132 | 80.1207 | 25690 | 74.0132 | 80.1207 | 25690 | 74.0132 | 0.0 | 80.1207 | 0.0 |
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+ | 0.4404 | 0.7769 | 5000 | 0.4112 | 74.3363 | 80.4688 | 25690 | 74.3363 | 80.4688 | 25690 | 74.3363 | 0.0 | 80.4688 | 0.0 |
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+ | 0.4835 | 0.7924 | 5100 | 0.4058 | 74.2935 | 80.4296 | 25690 | 74.2935 | 80.4296 | 25690 | 74.2935 | 0.0 | 80.4296 | 0.0 |
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+ | 0.5583 | 0.8080 | 5200 | 0.4043 | 74.3636 | 80.4871 | 25690 | 74.3636 | 80.4871 | 25690 | 74.3636 | 0.0 | 80.4871 | 0.0 |
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+ | 0.5009 | 0.8235 | 5300 | 0.4066 | 74.3519 | 80.4009 | 25690 | 74.3519 | 80.4009 | 25690 | 74.3519 | 0.0 | 80.4009 | 0.0 |
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+ | 0.4881 | 0.8390 | 5400 | 0.4030 | 74.4142 | 80.4285 | 25690 | 74.4142 | 80.4285 | 25690 | 74.4142 | 0.0 | 80.4285 | 0.0 |
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+ | 0.4428 | 0.8546 | 5500 | 0.3954 | 74.2779 | 80.3785 | 25690 | 74.2779 | 80.3785 | 25690 | 74.2779 | 0.0 | 80.3785 | 0.0 |
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+ | 0.4651 | 0.8701 | 5600 | 0.3993 | 74.3246 | 80.4433 | 25690 | 74.3246 | 80.4433 | 25690 | 74.3246 | 0.0 | 80.4433 | 0.0 |
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+ | 0.4067 | 0.8856 | 5700 | 0.4031 | 74.3480 | 80.5045 | 25690 | 74.3480 | 80.5045 | 25690 | 74.3480 | 0.0 | 80.5045 | 0.0 |
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+ | 0.4374 | 0.9012 | 5800 | 0.3958 | 74.6672 | 80.7476 | 25690 | 74.6672 | 80.7476 | 25690 | 74.6672 | 0.0 | 80.7476 | 0.0 |
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+ | 0.4645 | 0.9167 | 5900 | 0.3954 | 74.3986 | 80.5765 | 25690 | 74.3986 | 80.5765 | 25690 | 74.3986 | 0.0 | 80.5765 | 0.0 |
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+ | 0.4689 | 0.9323 | 6000 | 0.3971 | 74.6516 | 80.6983 | 25690 | 74.6516 | 80.6983 | 25690 | 74.6516 | 0.0 | 80.6983 | 0.0 |
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+ | 0.4239 | 0.9478 | 6100 | 0.3926 | 74.7373 | 80.7854 | 25690 | 74.7373 | 80.7854 | 25690 | 74.7373 | 0.0 | 80.7854 | 0.0 |
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+ | 0.4344 | 0.9633 | 6200 | 0.3919 | 74.6555 | 80.6953 | 25690 | 74.6555 | 80.6953 | 25690 | 74.6555 | 0.0 | 80.6953 | 0.0 |
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+ | 0.3875 | 0.9789 | 6300 | 0.3989 | 74.2507 | 80.3817 | 25690 | 74.2507 | 80.3817 | 25690 | 74.2507 | 0.0 | 80.3817 | 0.0 |
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+ | 0.4099 | 0.9944 | 6400 | 0.3944 | 74.4570 | 80.4510 | 25690 | 74.4570 | 80.4510 | 25690 | 74.4570 | 0.0 | 80.4510 | 0.0 |
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+ | 0.4074 | 1.0099 | 6500 | 0.3972 | 74.8151 | 80.7001 | 25690 | 74.8151 | 80.7001 | 25690 | 74.8151 | 0.0 | 80.7001 | 0.0 |
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+ | 0.3219 | 1.0255 | 6600 | 0.4074 | 74.6399 | 80.6479 | 25690 | 74.6399 | 80.6479 | 25690 | 74.6399 | 0.0 | 80.6479 | 0.0 |
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+ | 0.3923 | 1.0410 | 6700 | 0.4027 | 74.5699 | 80.5256 | 25690 | 74.5699 | 80.5256 | 25690 | 74.5699 | 0.0 | 80.5256 | 0.0 |
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+ | 0.359 | 1.0566 | 6800 | 0.3987 | 74.7334 | 80.6814 | 25690 | 74.7334 | 80.6814 | 25690 | 74.7334 | 0.0 | 80.6814 | 0.0 |
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+ | 0.3919 | 1.0721 | 6900 | 0.4035 | 73.9704 | 79.9235 | 25690 | 73.9704 | 79.9235 | 25690 | 73.9704 | 0.0 | 79.9235 | 0.0 |
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+ | 0.3784 | 1.0876 | 7000 | 0.3972 | 74.6283 | 80.6954 | 25690 | 74.6283 | 80.6954 | 25690 | 74.6283 | 0.0 | 80.6954 | 0.0 |
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+ | 0.3317 | 1.1032 | 7100 | 0.3943 | 74.5971 | 80.7187 | 25690 | 74.5971 | 80.7187 | 25690 | 74.5971 | 0.0 | 80.7187 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.50.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.1
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