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20230826065732

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - super_glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: '20230826065732'
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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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+ # 20230826065732
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+
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+ This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5294
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+ - Accuracy: 0.67
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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: 0.02
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 11
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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: 80.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 25 | 0.6448 | 0.4 |
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+ | No log | 2.0 | 50 | 0.7950 | 0.65 |
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+ | No log | 3.0 | 75 | 0.6181 | 0.54 |
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+ | No log | 4.0 | 100 | 0.5601 | 0.6 |
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+ | No log | 5.0 | 125 | 0.5816 | 0.42 |
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+ | No log | 6.0 | 150 | 0.5957 | 0.43 |
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+ | No log | 7.0 | 175 | 0.5331 | 0.61 |
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+ | No log | 8.0 | 200 | 0.5507 | 0.61 |
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+ | No log | 9.0 | 225 | 0.5438 | 0.62 |
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+ | No log | 10.0 | 250 | 0.5455 | 0.65 |
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+ | No log | 11.0 | 275 | 0.5141 | 0.65 |
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+ | No log | 12.0 | 300 | 0.5019 | 0.71 |
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+ | No log | 13.0 | 325 | 0.6824 | 0.7 |
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+ | No log | 14.0 | 350 | 0.5735 | 0.73 |
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+ | No log | 15.0 | 375 | 0.5578 | 0.69 |
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+ | No log | 16.0 | 400 | 0.5607 | 0.72 |
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+ | No log | 17.0 | 425 | 0.5974 | 0.71 |
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+ | No log | 18.0 | 450 | 0.8102 | 0.71 |
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+ | No log | 19.0 | 475 | 0.6757 | 0.73 |
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+ | 0.7598 | 20.0 | 500 | 0.5266 | 0.74 |
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+ | 0.7598 | 21.0 | 525 | 0.6271 | 0.69 |
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+ | 0.7598 | 22.0 | 550 | 0.6341 | 0.7 |
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+ | 0.7598 | 23.0 | 575 | 0.6874 | 0.7 |
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+ | 0.7598 | 24.0 | 600 | 0.5264 | 0.72 |
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+ | 0.7598 | 25.0 | 625 | 0.5148 | 0.73 |
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+ | 0.7598 | 26.0 | 650 | 0.5760 | 0.77 |
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+ | 0.7598 | 27.0 | 675 | 0.6581 | 0.71 |
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+ | 0.7598 | 28.0 | 700 | 0.6479 | 0.71 |
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+ | 0.7598 | 29.0 | 725 | 0.6960 | 0.69 |
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+ | 0.7598 | 30.0 | 750 | 0.6919 | 0.7 |
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+ | 0.7598 | 31.0 | 775 | 0.6421 | 0.68 |
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+ | 0.7598 | 32.0 | 800 | 0.5681 | 0.68 |
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+ | 0.7598 | 33.0 | 825 | 0.5631 | 0.68 |
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+ | 0.7598 | 34.0 | 850 | 0.5676 | 0.66 |
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+ | 0.7598 | 35.0 | 875 | 0.5389 | 0.68 |
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+ | 0.7598 | 36.0 | 900 | 0.6267 | 0.68 |
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+ | 0.7598 | 37.0 | 925 | 0.6107 | 0.65 |
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+ | 0.7598 | 38.0 | 950 | 0.5359 | 0.66 |
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+ | 0.7598 | 39.0 | 975 | 0.5741 | 0.67 |
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+ | 0.4266 | 40.0 | 1000 | 0.5928 | 0.69 |
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+ | 0.4266 | 41.0 | 1025 | 0.5307 | 0.68 |
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+ | 0.4266 | 42.0 | 1050 | 0.5909 | 0.66 |
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+ | 0.4266 | 43.0 | 1075 | 0.5733 | 0.66 |
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+ | 0.4266 | 44.0 | 1100 | 0.5561 | 0.66 |
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+ | 0.4266 | 45.0 | 1125 | 0.5600 | 0.69 |
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+ | 0.4266 | 46.0 | 1150 | 0.5228 | 0.66 |
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+ | 0.4266 | 47.0 | 1175 | 0.5383 | 0.7 |
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+ | 0.4266 | 48.0 | 1200 | 0.5643 | 0.69 |
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+ | 0.4266 | 49.0 | 1225 | 0.5493 | 0.7 |
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+ | 0.4266 | 50.0 | 1250 | 0.5576 | 0.7 |
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+ | 0.4266 | 51.0 | 1275 | 0.5543 | 0.68 |
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+ | 0.4266 | 52.0 | 1300 | 0.5615 | 0.69 |
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+ | 0.4266 | 53.0 | 1325 | 0.5358 | 0.67 |
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+ | 0.4266 | 54.0 | 1350 | 0.5405 | 0.69 |
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+ | 0.4266 | 55.0 | 1375 | 0.5327 | 0.69 |
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+ | 0.4266 | 56.0 | 1400 | 0.5645 | 0.67 |
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+ | 0.4266 | 57.0 | 1425 | 0.5240 | 0.67 |
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+ | 0.4266 | 58.0 | 1450 | 0.5402 | 0.67 |
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+ | 0.4266 | 59.0 | 1475 | 0.5495 | 0.68 |
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+ | 0.3249 | 60.0 | 1500 | 0.5624 | 0.66 |
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+ | 0.3249 | 61.0 | 1525 | 0.5513 | 0.67 |
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+ | 0.3249 | 62.0 | 1550 | 0.5537 | 0.68 |
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+ | 0.3249 | 63.0 | 1575 | 0.5444 | 0.68 |
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+ | 0.3249 | 64.0 | 1600 | 0.5553 | 0.68 |
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+ | 0.3249 | 65.0 | 1625 | 0.5221 | 0.68 |
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+ | 0.3249 | 66.0 | 1650 | 0.5136 | 0.68 |
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+ | 0.3249 | 67.0 | 1675 | 0.5231 | 0.69 |
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+ | 0.3249 | 68.0 | 1700 | 0.5305 | 0.69 |
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+ | 0.3249 | 69.0 | 1725 | 0.5278 | 0.68 |
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+ | 0.3249 | 70.0 | 1750 | 0.5440 | 0.66 |
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+ | 0.3249 | 71.0 | 1775 | 0.5411 | 0.67 |
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+ | 0.3249 | 72.0 | 1800 | 0.5346 | 0.69 |
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+ | 0.3249 | 73.0 | 1825 | 0.5241 | 0.67 |
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+ | 0.3249 | 74.0 | 1850 | 0.5425 | 0.67 |
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+ | 0.3249 | 75.0 | 1875 | 0.5213 | 0.67 |
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+ | 0.3249 | 76.0 | 1900 | 0.5405 | 0.66 |
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+ | 0.3249 | 77.0 | 1925 | 0.5251 | 0.67 |
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+ | 0.3249 | 78.0 | 1950 | 0.5300 | 0.67 |
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+ | 0.3249 | 79.0 | 1975 | 0.5285 | 0.67 |
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+ | 0.2946 | 80.0 | 2000 | 0.5294 | 0.67 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3